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Encord

Software Engineer, Applied AI

Posted 10 Days Ago
In-Office
San Francisco, CA, USA
150K-250K Annually
Mid level
In-Office
San Francisco, CA, USA
150K-250K Annually
Mid level
As a Software Engineer in Applied AI, you'll build and scale machine learning and computer vision solutions, collaborating with product and engineering teams to implement research into production. You'll experiment with ML technologies and solve engineering problems while contributing to hiring efforts.
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About us

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.

 

We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.

The role

We are looking for an experienced Applied AI Engineer to join our team and help us build and scale cutting-edge machine learning and computer vision solutions that power real AI workflows. You'll work hands-on across the full ML lifecycle — from experimenting with the latest models and techniques to integrating them into a production platform used by hundreds of AI teams worldwide.

This is a highly collaborative role where you'll partner closely with our product engineering and human data teams to turn complex algorithmic ideas into reliable, scalable features that customers love. Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.

If you're someone who thrives at the intersection of strong ML fundamentals and practical engineering, and wants to see their work make a direct impact at scale — this is the role for you.

What you'll do

  • Experiment with and adapt the latest ML technologies to fit into our existing tech stack

  • Solve idiosyncratic statistical, geometric, and engineering problems

  • Work closely with a full-stack tech team to assist implementation of research solutions into the product

  • Contribute to hiring additional talent to our rapidly growing team

  • Work with a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning

Who we're looking for

  • Hands-on and experimental — you're comfortable executing on projects end-to-end, running tests, and iterating based on what the data tells you

  • Collaborative by nature — you work closely with engineering and product teams to turn complex algorithmic ideas into reliable, scalable features

  • Driven to solve hard problems — you thrive at the intersection of strong ML fundamentals and practical engineering

  • Bonus: you've led or contributed to applied research teams and have relevant publications to show for it

Experience requirements

  • 3+ years of experience in machine learning engineering, with concrete examples of models or systems you've built and shipped

  • Strong experience in Python and ML libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai, and Keras

  • Strong foundation in mathematical programming, algorithmic problem solving, and applied machine learning

  • Bonus: experience in the AI/ML ecosystem and familiarity with computer vision

Why Encord

  • Competitive salary, commission, and meaningful equity in a high-growth startup

  • Clear, accelerated growth opportunities as the company scales rapidly

  • Strong in-person culture: 4–5 days/week in our newly launched North Beach loft office

  • Flexible PTO to fully recharge

  • 18 paid vacation days in the U.S. plus federal holidays

  • Annual learning & development budget

  • Comprehensive health, dental, and vision coverage

  • Frequent travel opportunities across the U.S., London, and Europe

  • Bi-annual company offsites, twice-weekly team lunches, and monthly socials

Encord San Francisco, California, USA Office

832 Sansome St, San Francisco, California, United States, 94111 1548

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