ML-Engineering Lead
Posted Jun 17 · 0 applicants
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The role in plain words
This role involves leading the full technical execution of machine learning projects from data acquisition to deployment. The engineer will collaborate with R&D departments to build ML models, tools, and intelligent agents, acting as a technical authority within the CTO's office. Day-to-day responsibilities include designing data collection strategies and deploying models for real-time field performance and autonomous research support.
- M.Sc. in Electrical Engineering, Computer Science, or a related technical field
- At least 7 years of experience building, training, and deploying ML models
- Proficiency in Python
- PyTorch
- TensorFlow
- Experience building AI agents (e.g., RAG systems, agentic workflows, or tool-calling implementations)
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Who this suits
This role suits an experienced ML professional with a master's degree and at least seven years of hands-on experience building and deploying models using Python and frameworks like PyTorch or TensorFlow. It is less ideal for junior candidates or those without experience managing end-to-end ML project execution.
Full job description
Original listing · kept for referenceDescription
What You Will Do:
• End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage—from data acquisition to deployment—meets our rigorous standards.
• R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
• Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
• Technical Authority: Act as a founding voice for ML implementation and strategy within the CTO’s office.
Qualifications:
• M.Sc. in Electrical Engineering, Computer Science, or a related technical field.
• At least 7 years of experience building, training, and deploying ML models.
• Proficiency in Python and deep familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow).
• Experience building AI agents (e.g., RAG systems, agentic workflows, or tool-calling implementations) is a significant plus.
• Proven ability to take a machine learning task from the research phase to a fully implemented and evaluated solution.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- M.Sc. in Electrical Engineering, Computer Science, or a related technical field, At least 7 years of experience building, training, and deploying ML models, Proficiency in Python, PyTorch, TensorFlow