Clarivate · 12 hours ago

Vice President, Machine Learning Engineering

Philadelphia, PA

Full-time

Remote

Director/Executive

$220K/yr - $280K/yr

8+ years exp

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Responsibilities

Work with the SVP of AI Product Transformation to identify highest leverage AI implementation opportunities across the Clarivate life sciences portfolio.

Assist in communicating AI investment and growth opportunities to the ELT, CEO, and potentially Board of Directors.

Formulate, communicate, and lead iteration of implementation approaches to achieve our AI project goals.

Hire, lead and manage a diverse, high-performing engineering team to execute against these goals.

Work closely with individual product owners and biologists to understand workflows, constraints, business value and opportunities at a granular level

Spend extensive time 'looking at data'.

Contribute meaningful amounts of code and/or documentation.

Mentor and develop a team of more junior, high performance, impact-oriented engineers and data scientists.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningAI Product DevelopmentEngineering ManagementLife Sciences KnowledgeSoftware DesignCommercial LLMsData PreprocessingModel EvaluationCross-functional CollaborationComputer ScienceMaster’s. in Computer ScienceProblem OwnershipMentoring EngineersHands-on Technical WorkTechnical Leadership

Required

Bachelor’s degree in Computer Science or related field (or equivalent applicable experience).

A seasoned technical leader, with 8+ years industry experience and 2+ years in engineering management.

Preferred

Past experience in delivering working ML / AI products.

Master’s or Ph.D. in Computer Science, Machine Learning, AI, or related field.

Experience collaborating with cross functional teams and product owners to identify, design, and implement systems that achieve business-level strategic goals.

Experience taking ownership and responsibility for critical problems end-to-end; from debugging a blocking Unicode encoding error to delivering project outcome slides.

Ability and willingness to build a granular, functional understanding a wide range of life sciences processes, product needs, and the information / data that power these needs.

Excited to do hands-on technical work but equally excited to lead technical teams to peak performance.

Experience working with current commercial LLMs like GPT-4.

Strong understanding of machine learning algorithms, data preprocessing, and model evaluation.

Experience designing software for the life science industry or for addressing problems in the life sciences.