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Senior Machine Learning Engineer, Generative AI Products

HBS

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Location:
United States , Boston

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

Not provided
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Job Description:

Lead comprehensive applications/web development for highly complex projects; typically work as part of a team to implement complex business solutions. Deliver strategic and expert coding; focus on overarching development strategy for a large, complex, multi-faceted application. May manage a number of projects simultaneously.

Job Responsibility:

  • Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents
  • Architect, build, maintain, and improve new and existing suite of GenAI applications and their underlying systems
  • Automate machine learning pipelines, monitor performance and costs, and optimize models by using techniques such as LoRA/QLoRA
  • Establish reusable frameworks to streamline model building, deployment and monitoring
  • Incorporate comprehensive monitoring, logging, tracing, and alerting mechanisms
  • Build guardrails, compliance rules and oversight workflows into the GenAI application platform, such as establishing approval chains for model updates and staged rollout for production releases
  • Develop templates, guides and sandbox environments for easy onboarding of new contributors and experimentation with new techniques
  • Ensure development of user-facing applications in the GenAI application platform is easy and safe by enforcing rigorous validation testing before publishing user-generated models and implement a clear peer review process of applications
  • Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value
  • Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps
  • Contribute to and promote good software engineering practices across the team
  • Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code
  • Actively contribute to and re-use community best practices
  • Monitor, debug, track, and resolve production issues
  • Work with project managers to ensure that projects proceed on time and on budget
  • Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs and prioritize performance improvements based on effort and impact
  • Complete other responsibilities as assigned

Requirements:

  • Minimum of seven years’ post-secondary education or relevant work experience
  • Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired
  • Minimum of five years’ software development experience with Python and SQL
  • Minimum of three years’ experience building pipelines to deploy NLP and deep learning models into production in a cloud environment
  • Minimum three years’ experience using PyTorch, Tensorflow, or MXNet, along with optimizing code for GPU clusters
  • Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools
  • Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications using tools such as NeMo
  • Experience with various embedding models and setting up and tuning vector databases to improve performance of semantic search and retrieval systems
  • Understand the underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs
  • Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka
  • a Linux environment
  • and at least one cloud provider solution (AWS, GCP, Azure)
  • Knowledge of data pipeline and workflow management tools
  • Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation
What we offer:
  • Generous paid time off including parental leave
  • Medical, dental, and vision health insurance coverage starting on day one
  • Retirement plans with university contributions
  • Wellbeing and mental health resources
  • Support for families and caregivers
  • Professional development opportunities including tuition assistance and reimbursement
  • Commuter benefits, discounts and campus perks

Additional Information:

Job Posted:
January 30, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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