London, United Kingdom - Hybrid

Agents for Software Development New start-up, Top team

Do you want to change how programming is done, and what software is? Are you an AI / ML engineer or researcher, experienced software engineer, or senior full-stack? Be one of the first to build the next generation of LLM coding agents!

Our system significantly surpasses the state of the art on coding benchmarks, handles codebases with thousands of files, and codes itself.

We are an experienced team, consisting of ex-DeepMind, ex-Microsoft Research, & seasoned entrepreneurs. While our system is still in stealth, we are backed by top venture-capital firms. Based in London, UK, in-person preferred, but can work remotely some of the time.

Email us about yourself, to meet Sean, Martin, Sam and Maxime at ICLR until Sunday: info@igent.ai

then book in-person meeting at NeurIPS

Remote

About Shopify Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can: Care deeply about what you do and about making commerce better for everyone Excel by seeking professional and personal hypergrowth Keep up with an unrelenting pace (the week, not the quarter) Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change Bring critical thought and opinion Embrace differences and disagreement to get shit done and move forward Work digital-first for your daily work

About the role Welcome to the engine room. Machine Learning Managers at Shopify drive impact by leading teams that build and fine-tune ML models to solve complex problems. This role involves making strategic decisions that influence millions of users daily, whether it's fraud detection, revenue predictions, or product recommendations. We’re all in on AI, and the possibilities for good are endless. Why you’ll love working at Shopify

Lead elite ML teams. Guide world-class ML engineers who are focused on building the future.

Agency at the helm of the rocket-ship. Make key decisions on how our ML models are developed, impacting millions of daily users.

Drive strategic ML projects. Oversee the development of ML initiatives — balance ruthless prioritization and making the right tradeoffs.

Cultivate technical excellence. Foster a culture of innovation, collaboration, and continuous improvement within your team.

Remote

About Shopify Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can: Care deeply about what you do and about making commerce better for everyone Excel by seeking professional and personal hypergrowth Keep up with an unrelenting pace (the week, not the quarter) Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change Bring critical thought and opinion Embrace differences and disagreement to get shit done and move forward Work digital-first for your daily work

About the role Code is core. Software engineers at Shopify craft the code that powers commerce. They build extendable products that scale the entire commerce stack, from creating the best buying experiences to developing innovative 0-1 financial products, and enhancing developer tools. They fail fast, reject the orthodox (unless ideal), and code solutions that enable merchants to succeed at the infinite game of entrepreneurship.

Why you’ll love working at Shopify Biggest Rails app in the world. Love Rails? Us too. You get to see how Shopify handles the largest Rails app in the world — and continuously make it better.

Solve problems at a massive scale. Work on complex engineering problems, with full ownership, on products real people use every day.

Ship at high speeds. Engineers collaborate cross-discipline on projects that ship weekly (not quarterly). They break things, iterate, and constantly pursue the green path of development.

Meet our CEO in the code. You’ll hear from our CEO, Tobi, regularly. He sets the direction, learns by coding, and is deeply passionate about the details.

Ready to craft your next masterpiece in code? Join the team that's making commerce better for everyone.

Cambridge-MA (Boston)

We are looking for an ML Scientist to join our all-atom modeling efforts. We are in person at NeurIPS, please contact oviessmann@flagshippioneering.com (Olivia Viessmann) to meet up and chat about roles.

The Role

Pioneering Intelligence (PI) is a Flagship initiative that develops AI/ML-based platforms for applications in life sciences and beyond. We are seeking a Senior Machine Learning Scientist or Engineer with hands-on experience implementing novel methods in generative biomolecular design, large model scaling, data curation, and data engineering.

Responsibilities

• Be part of a developer team: Work with the PI team to develop the next generation of biomolecular generative models across proteins, small molecules, nucleic acids, and more.
• Hands-on dev: Code the new ideas you develop with the team. Train, test, and scale models, with opportunities to validate in the lab.
• Make an impact: The models you develop will be leveraged by multiple Flagship ventures. Work with biologists and chemists to turn your in-silico work into real-world impact.

Qualifications

• PhD in CS, AI/ML, Physics, Biophysics, Biochemistry, Comp Biology, or related.
• Experience developing, implementing and training deep learning models.
• Experience in curation, processing and data engineering of TB-sized datasets.
• Experience with large scale training over multiple nodes on cloud infra.
• Fluent in Python, familiar with PyTorch and Git.

Preferred Experiences:

• Implementing generative models such as LLMs, diffusion, and flow-matching for proteins or small molecules.
• Constructing, annotating, and serving large databases of biomolecular data.
• Biomolecular design models and tools such as RFDiffusion, ProteinMPNN, AlphaFold, ESM, DiffDock, etc.
• ML software development and cloud services, e.g., Docker, AWS Batch, Step Functions, EKS, AWS ParallelCluster, etc.
• 3+ years industry experience.

About Flagship

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Applications are invited from those with excellent machine learning training to work in the laboratory of Prof. Albert Montillo ( www.montillolab.org ) at the University of Texas Southwestern, in Dallas, TX. The long-term goal of the lab is to develop fundamental advances in the theory of machine learning (ML) and causal analyses and their application to guide prognoses and clinical treatment decisions and elucidate treatment mechanisms with applications in neurology and oncology. The lab analyzes multimodal data, including medical images, clinical, multi-omic, and speech data.

Multiple positions are available in these areas: 1. Explainable, causal machine learning 2. Neuroimage and medical image analysis using foundation models 3. Foundation models for image-guided cancer surgery 4. Computational linguistics for speech impairment characterization

Read more about the roles here: https://montillolab.org/#PostdoctoralFellowshipPositions

We are part of major ongoing research projects investigating aging, dementia, movement disorders, and brain stimulation, which generate an unparalleled trove of medical images (multi-contrast MRI, EEG, MEG), clinical and multi-omic data (genomics, metabolomics), brain biomarkers, and speech recordings. The successful candidate will join a group of friendly and productive machine learning researchers in the departments of Bioinformatics & Biomedical Engineering and will have an opportunity to work with world-class neurologists, psychiatrists, surgeons, and neuroscientists. Recent work from the group includes the development of fundamental machine learning frameworks and their applications for accurate prognoses and clinical decision guidance: K. Nguyen et al., IEEE TPAMI, 2023; Berto et al., Nat Comm, 2023; Mellema et al., NeuroImage:Clinical, 2024; Treacher et al., NeuroImage, 2022; K. Nguyen et al., Bio. Psychiatry, 2022; S. Nguyen et al., MICCAI 2020.

Our lab is situated in two rapidly growing departments committed to an entrepreneurial approach to research, with a flexible work culture and competitive compensation. Our university provides world-class computational resources (portal.biohpc.swmed.edu ) and research-dedicated high quality imaging (utsouthwestern.edu/departments/airc ). We have rich experience developing the theory of deep learning, integrating ideas from causal discovery, Bayesian modeling, and deep learning, to enable improved performance, generalization, and confound mitigation. In our ML applications, we develop machine learning-based metrics and predictive models from imaging, multi-omic, and speech data that predict trajectories in neurological and oncology applications, fusing domain expert knowledge with probabilistic, interpretable deep learning.

Requirements

The ideal candidate will have:
- A PhD or MD/PhD in machine learning, computer science, biomedical or electrical engineering, statistics, physics, or any related field providing a firm machine learning background. - Publications demonstrating algorithmic innovation. - Strong programming ability and mathematical training.

Previous experience in biomedical applications of machine learning, experience in image or speech analysis, explainable AI, Bayesian and graph neural networks, or causal discovery/inference is advantageous, but not mandatory. We are particularly interested in hiring at least one fellow with a rigorous statistical background.

Apply

The position is available immediately and we will accept applications until the position is filled; early application is strongly recommended. Apply by email to Dr. Montillo (albert.montillo@utsouthwestern.edu) and include: 1. Your CV 2. A statement of research accomplishments and interests 3. Contact information for 3 references

HYBRID

About This Role:

Crusoe Cloud is seeking a highly skilled Staff Solutions Engineer to work closely with our most strategic customers as they deploy AI/ML workloads on Crusoe Cloud. This is a hands-on technical role, where your deep expertise in cloud infrastructure and AI technologies will be instrumental in ensuring our customers’ success. You will act as a trusted advisor, guiding customers through the deployment and optimization of their AI workloads, ensuring they leverage Crusoe’s platform to its fullest potential.

This role offers an opportunity to engage directly with customers, support pre-sales and post-sales efforts, and contribute to building reusable, scalable solutions. You will collaborate with cross-functional teams to drive technical excellence and customer satisfaction.

Core Responsibilities

Technical Advisor to Customers: Act as a key technical resource for customers, providing expert guidance on deploying and optimizing AI/ML workloads on Crusoe.

Hands-On Solution Development: Work closely with customers to scope, deploy, and optimize AI workloads, leveraging modern cloud infrastructure tools such as Docker, Kubernetes, and Terraform.

Support Pre-Sales and Post-Sales Engagements: Partner with Sales and Customer Success teams to ensure smooth customer onboarding, from proof-of-concept (PoC) to full deployment, and provide technical support during the post-sales phase.

Optimize AI Workloads for Performance: Lead efforts to benchmark, validate, and optimize AI/ML workloads for performance and efficiency, ensuring customers achieve the best possible outcomes on Crusoe.

Collaborate Across Teams: Work closely with Engineering and Product teams to influence Crusoe’s roadmap based on customer feedback and technical requirements, ensuring continuous platform improvement.

Customer-Facing Demonstrations and Education: Lead technical demonstrations, workshops, and discussions to educate customers on the benefits of Crusoe and how to best utilize the platform for their AI workloads.

Evangelize Crusoe Solutions: Contribute to technical content such as case studies, blog posts, and solution briefs, showcasing successful customer deployments and best practices.

Location United Kingdom - Remote, London United States - Remote, San Francisco, New York Europe - Remote Canada - Remote, Toronto

Why this role?

At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI.

As a Member of Technical Staff with a focus on Multimodal AI, you will:

-Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text, speech, and vision.

-Conduct research and experiments on our advanced compute infrastructure, exploring novel ideas in multimodal representation learning, transfer learning, and more.

-Collaborate closely with our world-class teams, learning from and contributing to their expertise in the field.

Reporting to the Chief Technology Officer, the HPC Systems Engineer will spearhead the design, deployment, and optimization of our high-performance computing (HPC) systems with a focus on HPC clustering, Kubernetes, Slurm, and management tools. The ideal candidate will seamlessly blend traditional HPC solutions with modern container orchestration, ensuring a versatile and scalable computing environment that can be offered to our customers.

Responsibilities

Lead the deployment and maintenance of HPC clusters, ensuring they operate effectively and maximise availability Integrate and manage HPC software components such as Kubernetes, Slurm, cluster management software, and any infrastructure required to operate the HPC environment Stay abreast of advancements in HPC, Kubernetes, and associated technologies, bringing innovations into our operations and product options. Collaborate with technical teams to establish and implement best practices for system maintenance and optimization. Draft comprehensive documentation, including system designs, operational procedures, and best practice guidelines. Facilitate the selection and integration of relevant management tools to monitor, troubleshoot, and enhance HPC operations. Provide technical leadership and training to other team members, fostering an environment of continuous learning and improvement. Desired Skills, Qualifications and Competencies include:

Minimum of 5 years of experience in HPC system architecture with proven expertise in designing, deploying, and managing HPC clusters. Extensive knowledge of Kubernetes, with a focus on its integration within HPC environments. Hands-on experience with the Slurm workload manager and its intricacies. Familiarity with HPC management tools and software, ensuring efficient system monitoring and troubleshooting. Proven track record of resolving complex system challenges and enhancing operational performance. A Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Relevant certifications in Kubernetes, HPC technologies, or system architecture are advantageous. Understanding of cloud platforms and their integration into HPC ecosystems. Deep knowledge of network and storage solutions commonly used in HPC setups. Key Attributes

Analytical mindset, adept at envisioning and designing intricate systems. Collaborative approach, with the ability to work effectively with diverse technical teams. Excellent communication skills, translating complex technical concepts into understandable terms for varied audiences. Detail-oriented focus, ensuring systems are both robust and efficient. Continuous learner, keen to stay updated with rapid technological evolutions in the HPC and Kubernetes domains.

At Capital One, you will help bring the transformative power of emerging AI capabilities to advance our mission to change banking for good and help improve the financial lives of millions of customers.

Remote

About Shopify Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

About you Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

Before you apply, consider if you can: Care deeply about what you do and about making commerce better for everyone Excel by seeking professional and personal hypergrowth Keep up with an unrelenting pace (the week, not the quarter) Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change Bring critical thought and opinion Embrace differences and disagreement to get shit done and move forward Work digital-first for your daily work

About the role Product data scientists at Shopify tell the story of the building blocks of commerce. They guide product development and improvement by partnering across disciplines and influencing a culture of data-informed [not data-driven] decision making. Our data scientists uncover the insights that inform how Shopify decides on what products to build and how to build them.

Why you’ll love working at Shopify Seek objective truth. Our goal is to search for the objective truth through analysis so we can challenge assumptions and judgements. Help with the big decisions Apply analytical, statistical, and technical skills to drive insights that inform business actions and product decisions. Leverage advanced analytics tools. Use cutting-edge techniques like regression, segmentation, and experimentation.

Ready to turn data into product discovery? Join the team that's making commerce better for everyone.

Sunnyvale, CA - Hybrid

LinkedIn is looking for a Distinguished Engineer, with deep expertise in Machine Learning & AI systems, to provide thought leadership for the Data & AI organization.

As a Distinguished Engineer at LinkedIn, you will architect and lead the next generation of AI solutions that power everything LinkedIn does. From consumer to enterprise, from search to recommendation, from optimization to building our foundational AI technologies, LinkedIn relies on innovative AI research and applications that you will help us build.

As a key leader in the Core Data & AI organization, you will lead research, design algorithms, build software, anticipate and influence the state of the art in the industry, and leverage and create open source software in the process.

Basic Qualifications: 10+ years of work experience in machine learning/AI 6+ years of technical leadership experience B.A./B.S. degree or higher or equivalent experience

Preferred Qualifications: PhD in a relevant field or related discipline (machine learning, statistics, computer science etc.), or equivalent research experience Strong academic credentials with publications in top-tier journals and conferences Experience in designing and implementing AI systems at scale to solve complex business problems Experience of technical leadership guiding and mentoring top engineering and operations talent Experience leading high-impact, cross-company initiatives

McGovern Institute for Brain Research at MIT, Cambridge MA, USA

November 13, 2024

Two Postdoctoral Positions

Elucidating the neurobiological and physiological control principles of brain-body interactions

Jazayeri and Wang Labs, MIT

The Position Two postdoctoral positions are available in the Jazayeri and Wang lab to join a new research project to elucidate the neurobiological, physiological and computational control principles of brain-body interactions.

The Project Wang’s lab has a longstanding research program focused on the neurobiology of brain-body interactions in mice. Jazayeri’s lab has worked extensively on how the brain instantiates internal models for cognition using a combination of experimental work and control theory. This project, which draws from expertise in the two labs aims to bring together experimental work in humans, nonhuman primates, and rodents with theoretical and computational work based in the theory of control systems to develop a deep understanding of the control principles that govern the neurobiology and physiology of bidirectional brain-body interactions. The project is an excellent launching pad for a research career in academia or industry at the bleeding edge of embodied neuroscience.

Your Primary Role This is a team project with two postdocs and possibly additional graduate students. We are looking for highly motivated and talented individuals to work as part of a team with multidisciplinary expertise in neurobiology, body physiology, engineering, and modeling. All team members may be active contributor to all aspects of the science. Here are some example problems you may work on:

· Perform behavioral and/or physiology experiments in humans, monkeys, or rodents. · Analyze large-scale data recorded from experimental subjects. · Develop a control-theoretic model constrained by experimental measurements in the brain and body.

Why Should You Join the Brain-Body Team? · We will be working at the cutting edge of embodied neuroscience. · We may discover the fundamental control principles of brain-body interactions. · Our work may enable exciting applications in medicine. · We will share the data openly and lead the way in collaborative science. · The project will open the door to exciting career trajectories in academia and industry.

Job Requirements Applicants must have a PhD or equivalent degree in Natural Sciences, Computational Neuroscience or Engineering. The applicant is expected to have demonstrated background in at least two of the following fields: systems neuroscience, neurotechnology, computational neuroscience, machine learning. Strong analytical and coding skills are necessary. Prior research on the neurobiology of brain-body interactions is highly valued.

The position is intended for 3 years or more and will be renewed annually. The salary will be determined based on merit. Individuals who have faced unexpected career challenges are highly encouraged to apply.

Applicants should submit a detailed cover letter and CV. We are looking for someone who is passionate about science, understands the importance of the problem we want to tackle, and has the requisite skills to help the team. The cover letter should explain why the project interests you and highlight your relevant expertise. To apply or ask questions, please send an email to both Mehrdad Jazayeri and Fan Wang at MIT (mjaz@mit.edu; fan_wang@mit.edu).

Hiring Globally - Miami, New York, London, Hong Kong, Singapore and Sydney

Quantitative Researchers play a key role in this mission by developing next-generation models and trading approaches for a range of investment strategies. You’ll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.

Your Objectives Use statistics, machine learning or AI (e.g. deep learning, NLP) to extract patterns from various kinds of datasets through innovative and rigorous research
Implement algorithms in high-quality code
Work with large data sets, including unconventional and unstructured data sources
Back-test models and document research findings

Your Skills & Talents PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis, pattern recognition, NLP) Prior experience working in a data driven research environment Experience with translating mathematical models and algorithms into code (Python, R or C++) Independent research experience Ability to manage multiple tasks and thrive in a fast-paced team environment Excellent analytical skills, with strong attention to detail

By applying you will be considered for Citadel and Citadel Securities.

Citadel is one of the world’s leading alternative investment managers. We manage capital on behalf of many of the world’s preeminent private, public and nonprofit institutions. We seek the highest and best use of investor capital in order to deliver market leading results and contribute to broader economic growth. For over 30 years, Citadel has cultivated a culture of learning and collaboration among some of the most talented and accomplished investment professionals, researchers and engineers in the world. Our colleagues are empowered to test their ideas and develop commercial solutions that accelerate their growth and drive real impact. For more information, visit Citadel.com.

Citadel Securities is a leading global market maker that provides institutional and retail investors with the liquidity they need to execute transactions in all market conditions across a broad array of equity and fixed income products. At Citadel Securities, the brightest minds in finance, science and technology use next-generation analytics to solve the market’s most critical challenges, turn big ideas into real-world outcomes and accelerate their careers. For more information, visit CitadelSecurities.com.

Location Palo Alto, CA, USA

What to Expect

Tesla is seeking exceptional Machine Learning Interns to help build large scale models to drive the future of autonomy across all current and future generations of Tesla AI products. You will work on a lean team without boundaries and have access to one of the world’s largest training clusters with a data engine that constantly generates new information for improving our models. Most importantly, you will see your work repeatedly shipped to and utilized by millions of Tesla’s customers.

We are seeking Interns in the following AI disciplines:
- Train large-scale foundation and generative models that are optimized for performance and latency
- Improve data engine for large scale and high-quality dataset curation - Reinforcement Learning for instilling objectives and improving overall robustness - Design compound AI systems for better planning and reasoning

What You’ll Do

• Applied research in the areas of Foundation Models, including but not limited to computer vision, large language models and generative modeling
• Work on cutting-edge techniques in AI - multi-task learning, video networks, multi-modal generative models, imitation learning, reinforcement learning, semi-supervised learning, self-supervised learning
• Explore and implement novel AI tooling and techniques for efficient training and fine-tuning of large-scale models
• Collaborate with a team to apply research findings to real-world challenges, ensuring high-quality system integration within existing platforms
• Experiment with data generation and network driven data collection approaches to enhance the diversity and quality of training data
• Ship production quality, safety-critical AI software

Vancouver, Canada

Who we are We’re redefining how humans interact with massive amounts of imagery & video.

What that means We’re building a near future where people can get information out of imagery at scale without building their own ML models. Collaborating with users around the world, our AI research and products change how people monitor and protect our oceans.

Our core technology: Find Anything & Video Search. We make it possible to find anything in imagery/video, without having seen it in training. Advancing the field of computer vision, pioneered in-house at OnDeck and published at one of the world’s most distinguished AI conferences (NeurIPS).

Backed by National Geographic, the Environmental Defense Fund, Canada’s Ocean Supercluster, and many more, we stand at the forefront of AI for ocean conservation & protection. Our software has been deployed by governments, Indigenous nations, scientists, NGOs, and industry around the world.

What you’ll be doing We’re excited to be pushing the boundaries of what is possible in computer vision: creating systems that can detect objects never before seen in training (by using external knowledge) and searching for anything in thousands of hours of video footage with natural language search.

This means on top of tweaking our standard vision methods and engineering ML and data pipelines, you’ll get to work on cutting-edge open-domain vision methods and even contribute to original research and papers submitted to conferences. Your responsibilities will encompass: - Developing state-of-the-art machine learning models that can reason about visual data and retrieve relevant answers from external knowledge sources. - ML engineering of systems that ingest large volumes of visual data, and allow finding complex sequences of events or objects never seen in training data. - Working on the entire ML lifecycle, from conducting research and developing innovative models to productionizing them and quantifying their real-world improvements. - Contributing to automated model lifecycle management, which takes models to production, handling large volumes of video footage while undergoing updates smoothly.

You will have significant ownership over mission-critical development, propelling us as a first-to-market at scale. You’ll also get to work on cutting edge applied ML research and even publish your work at top conferences. In return, we’re looking for commitment to and excitement for OnDeck’s journey at the forefront of ocean tech, climate tech and open-domain computer vision.