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AI / Machine Learning Engineer
Job Description
Required Skills:
Knowledge of artificial intelligence ideally with applications on multimedia, cyber security or adversarial machine learning / AI security experience. Applied AI/ML knowledge - solid graduate-level coursework or equivalent work experience applying machine-learning theory, deep learning, NLP, computer-vision, graph analytics, or adversarial/AI-assurance techniques. Proficient Python programming - comfortable writing clean, modular, and testable code; expert-level use of deep-learning frameworks (PyTorch, TensorFlow, etc.), data-science stacks (NumPy, pandas, SciPy, etc.), and hands-on experience with agentic/LLM-oriented toolkits (e.g., MCP). Operating in a rapid research-to-prototype pipeline - demonstrated ability to take a cutting-edge research concept, design an experimental plan, implement a functional prototype, and iterate based on quantitative evaluation. Experience with benchmark datasets and realistic metrics (e.g. latency, accuracy, robustness) is a plus. Software-engineering best practices - strong Git workflow (branching, pull-requests, code reviews), continuous-integration testing, environment reproducibility (e.g., conda, virtualenv). Ability to document code, write reproducible experiment notebooks, and maintain versioned releases.Desired Skills:
Ability to read, evaluate, and implement state-of-the-art AI research papers. Problem-solving & analytical mindset - can decompose novel, ill-defined problems, propose multiple solution paths, and select the most promising approach based on empirical evidence. Detail-oriented, able to multi-task, with the ability to work autonomously with minimal supervision. Effective written and oral communication skills in technical environments, technical reports, internal wiki pages; delivers clear demo presentations and briefings to both technical audience and senior mission stakeholders.group id:
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Based on Massachusetts data
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$133,397 / year median in Massachusetts