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Company

Original Job Post

Harvard Business Publishing · 1 week ago

Machine Learning Engineer

United States

Full-time

Remote

Senior Level

$120K/yr - $135K/yr

7+ years exp

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Responsibilities

Work with the backend engineering practice and senior stakeholders on all the decisions and designs that drive the learning products and software solutions that affect the strategic direction of the company.

Collaborate with technical staff and product managers to determine requirements and help define and build the next generation content recommendation engine and GenAI integration tools that offer personalized experiences.

Be involved in discussions on how ML can affect other upstream (content development, content tagging, taxonomy) and downstream services (search, data storage, analytics). Develop high-level design specifications with particular attention to system integration and feasibility.

Contribute to many ML/AI related initiatives and systems at HBP over time.

Communicate broadly all concepts and guidelines to the development teams and be able to translate technical concepts to a non-technical audience.

Contribute hands-on code for this new service and ensure the product architecture is adaptable and evolves to meet the changing needs of the business.

Research, develop, and implement high-performance services for content recommendation and GenAI integration systems.

Regularly evaluate and recommend tools, technologies, and processes to support a portfolio of modeling engines designed for learning products.

Build extremely efficient and reliable data pipelines using behavioral data and analytics.

Investigate new and developing technologies in the industry and determine how to leverage these new technologies in software applications.

Provide regular and timely written and verbal communication on progress and status.

Develop and implement strategies to handle ML/GenAI monitoring, including detection of model/data drift, model performance, and model consumption patterns.

Participate in the design, development, and deployment to production of GenAI applications that use modern LLMs (OpenAI, Anthropic, etc.).

Troubleshoot code-level problems quickly and efficiently.

Qualification

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PythonJavaSpringHibernateSecurityData PrivacyScikit-learnTensorFlowPyTorchOpenAIAnthropicLlamaRAGArchitectural ApproachLLMsStructured DataUnstructured DataApplication ContainerizationDockerAWS ECSAWS ECRSystem Monitoring ToolsNew RelicSplunkAutomated Testing FrameworksProblem-SolvingHard WorkingOrganizationalLeadershipCommunication

Required

7+ years of proven experience in an ML/AI architect role with a focus on GenAI, data analysis, and machine learning algorithms and models

Practical experience in developing ML models using Python (knowledge of Java and Spring/Hibernate a huge plus)

Experience building applications that conform to high standards for security and data privacy

Experience with common ML/AI libraries (e.g. scikit-learn, TensorFlow, PyTorch) and current LLMs (OpenAI, Anthropic, Llama)

Hands-on working experience with RAG architectural approach

An understanding of how state-of-the-art LLMs can be induced using both structured and unstructured data

Experience and understanding of application containerization and services (Docker, AWS ECS, AWS ECR)

Experience applying system monitoring tools (e.g., New Relic, Splunk)

Experience with automated testing frameworks

Excellent organizational, leadership, and communication skills and a sense of ownership and drive

Preferred

If you’ve worked with an online learning organization and have expertise in implementing ground-up recommenders for learning systems, we want to talk to you.