Senior Machine Learning Engineer

Technology Staffing Group; Genf; Vor Ort; EUR 80’000 - 120’000; Vollzeit

Zusammenfassung

Join a leading global player in the energy sector as a Machine Learning Engineer. Engage in impactful projects, collaborating with a dynamic team to develop ML solutions that drive business success. Leverage your expertise in Python and data science to enhance data-driven decision-making across the organization.

Qualifikationen

• Masters degree in relevant field; Ph.D. is a plus.
• 3-5+ years of experience in developing ML models.
• Strong understanding of deep learning and NLP techniques.

Aufgaben

• Design and deploy machine learning models and systems.
• Collaborate with cross-functional teams to gather requirements.
• Integrate ML solutions into existing platforms for enhanced scalability.

Kenntnisse

Python

ML Fundamentals

Problem Solving

Communication Skills

Ausbildung

Masters degree in Computer Science, Data Science, Machine Learning

Tools

TensorFlow

PyTorch

Docker

AWS

Jobbeschreibung

About Our Client:

Our client is a leading global player in the energy sector, with a dynamic, entrepreneurial culture that empowers talent to thrive. The company offers opportunities to work on impactful projects in major energy hubs, with a strong commitment to growth in renewables and innovative infrastructure solutions. They provide exceptional support and development, making this the perfect environment to advance your career and shape the future of energy.

We are looking for an experienced Machine Learning Engineerto join the data science and machine learning team. The ideal candidate will collaborate closely with data and machine learning specialists, software engineers, and commercial teams to deliver machine learning models and applications.

Core Responsibilities

• Act as a proactive and collaborative member of a high-impact team focused on applying data science to real-world energy challenges.
• Lead the design, development, and deployment of machine learning models and systems.
• Collaborate with cross-functional technology teams to gather business requirements and ensure alignment with strategic objectives.
• Integrate ML and AI solutionsincluding generative AIinto existing platforms to enhance usability, adoption, and scalability.
• Participate in code reviews, experimentation, and tooling decisions to drive team velocity and technical quality.
• Share knowledge and build internal machine learning capabilities through peer collaboration and mentorship.
• Engage with commercial and operational teams to identify new opportunities for data-driven value creation.

Essential Qualifications

• Masters degree in Computer Science, Data Science, Machine Learning, or a related field; Ph.D. is a plus.
• Proficiency in Python, with clean, modular, well-documented coding practices.
• 3-5+ years of hands-on experience developing and deploying machine learning models in production environments.
• Strong understanding of ML fundamentals, including deep learning, generative models, and NLP techniques.
• Practical experience with ML libraries such as TensorFlow, PyTorch, or Transformers.
• Familiarity with cloud platforms (especially AWS) and containerization (Docker).
• Strong problem-solving skills and the ability to work both independently and collaboratively.
• Excellent communication skills, with the ability to explain complex technical topics to non-technical stakeholders.

Desired Experience

• Prior experience in the energy, commodities, or trading industry, with knowledge of financial markets and trading principles.

• Expertise in time-series modeling (machine learning and econometrics).

• Experience integrating ML systems into interactive dashboards (e.g., Dash, Streamlit).
• Application of diverse machine learning techniques to real-world business use cases.
• Experience in enterprise software development, including systems design, version control, and code reviews.
• Familiarity with data orchestration tools (Airflow, Dagster) and cloud-based ETL/ELT pipelines.

• Awareness of CI/CD pipelines and deployment automation best practices.

Personal Attributes

• Self-motivated, results-oriented, and excited to see tangible business impact from their work.
• Strong communication, both verbal and written, and a collaborative mindset.
• Curious, creative, and adaptablecomfortable working in a dynamic, fast-moving environment.
• Methodical and organized, with a strong attention to detail in code, experiments, and design.
• Open-minded and willing to both learn from others and share their own knowledge.
• Interest in the energy and commodities space and a desire to help shape the industrys digital transformation.

• High level of integrity and a non-political, team-first attitude.

Your Data

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