engineering
Posted 1 weeks agoSoftware Engineer, Applied AI
at Encord
San Francisco, United StatesOn-site
You are nearing today's limit. Upgrade for unlimited access.
Requirements
- 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.
- 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.
- 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
- 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
- Experience requirements - 3+ years of