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Machine Learning Engineer

TechnipFMC - Krakow

Posted Jun 12, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Mental health support
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

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About this role

Machine Learning Engineer Krakow Job Purpose TechnipFMC leads the transformation of the energy industry by transforming our clients' project economics through fully integrated projects, products, and services. Making robust decisions efficiently and consistently by using data about our products, processes, and operations is a key competency for our business to achieve our true north. In this context, the business is developing its Advanced Analytics capability with the aim of better leveraging our data to deliver new insights, value and smarter ways of working across our value stream. Machine Learning Engineering is a key discipline in this context that focuses on designing, building, and deploying scalable machine learning systems and infrastructure to enable data-driven decision-making and innovation. This role is for a Machine Learning Engineer who will be a member of the Advanced Analytics team (within Software Services) that is responsible for developing the company's data analytics strategy and roadmap. Job Description Health, Safety & Environment: Complete mandatory HSE courses and implement any recommended safety actions efficiently. Be a consistent role model in relation to safety practices with a commitment to the importance of safety Performance & Delivery: Optimize model performance through hyperparameter tuning, feature engineering, and algorithm selection. Collaborate with data scientists to translate prototypes into production-ready solutions. Design and implement scalable machine learning pip

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