Machine Learning Engineer

Design, develop, and improve software technology used in robotic applications. Reimagine robot prototypes to solve the most important and fundamental challenges in AI and robotics. Architect scalable infrastructure for model training and data processing of high-performance pipelines. Duties include: 

1. Design systems to explore solutions for real world problems using model-based and data-driven techniques;

2. Train, deploy, and sustain machine learning (“ML”) models on both cloud and on-prem infrastructure to enhance robotic capabilities;

3. Build and refine ML pipelines, encompassing every lifecycle phase from training and evaluation to optimization and deployment;

4. Design, test, and implement robust model architectures suited for production in partnership with research and engineering teams;

5. Elevate code quality through regular peer reviews and champion best practices in our software processes;

6. Engage in our research environment to stay at the cutting edge of advancements in ML architectures, frameworks, and applications.

Minimum Requirements:  

A Master’s degree (or foreign equivalent) in Computer Science, Robotics Engineering, or a closely related discipline plus 4 years of experience in a machine learning-related occupation. 

Experience must include the following, which may have been gained concurrently: 

1) 4 years of experience utilizing C++ or Python to develop and implement high performance machine learning models and algorithms in production environments;

2) 4 years of experience with git, issue tracking, CI/CD, and modern software engineering practices to develop, test, and review scalable and maintainable code and pipelines that support the deployment and operation of machine learning systems;

3) 4 years of experience using machine learning algorithms, including Linear and Logistic regressions, Decision tree, Naive Bayes, KNN, K-means, and Random forest, to select, implement, and evaluate classical machine-learning models;

4) 4 years of experience with Machine Learning Ops, including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, and continuous learning, to develop, maintain, test, and deploy production-grade machine-learning systems;

5) 4 years of experience creating orchestration workflows using tools, including AirFlow, to design and implement scalable and fault-tolerant data and machine learning workflows for automated model training and evaluation;

6) 3 years of experience using deep-learning techniques in NLP and Computer Vision to design and implement robust deep-learning model architectures suite for production environments;

7) 2 years of experience using data science tools, libraries, and frameworks, including Scikit-learn, NumPy, SciPy, Pandas, TensorFlow, and PyTorch to develop high-throughput, end-to-end machine learning pipelines, from training and evaluation to optimization and deployment;

8) 2 years of experience in robotics engineering;

9) 2 years of experience using robotics frameworks and libraries, including ROS, OpenCV, and Open3D, to implement, test, and deploy robotics algorithms and to support robotics systems in production.

Job site: 145 Broadway, Cambridge, MA 02142. Full-time. Salary: $186,160 to $237,900. 

To apply, email cover letter and resume, referencing Req. #061454-372, to [email protected].

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