Senior ML Engineer
5y relevant experience
EU engineers, ready to place with your US clients
Pre-screened on AI. Remote B2B contracts. View 5 full profiles free — AI score, skills report, interview questions included.
Executive Summary
Exceptional ML engineer candidate with rare combination of deep theoretical knowledge and proven production experience. PhD-level expertise in modern ML with 280+ citations, plus 3+ years building production ML systems at startups including founding technical role. Strong match for technical requirements with Python, PyTorch/TensorFlow, AWS, and Docker experience. Led teams, shipped business-critical models, and has patent for ML-assisted DNA assembly. Main gaps are explicit Kubernetes and MLOps pipeline experience, but strong fundamentals and rapid learning ability evident from career progression. High potential for technical leadership and innovation in production ML systems.
Top Strengths
- ✓PhD-level ML expertise with 280+ citations and publications in top-tier venues (CVPR, AAAI, TPAMI)
- ✓Hands-on production ML experience with modern stack (PyTorch, transformers, AWS, Docker)
- ✓Proven ability to lead technical teams and deliver business-critical ML systems
- ✓Experience with cutting-edge areas relevant to company needs (generative AI, multimodal models, robust ML)
- ✓Strong track record of innovation including patents and 10% performance improvements on production models
Key Concerns
- !Limited explicit Kubernetes and MLOps pipeline experience mentioned
- !Transition from research-heavy background to pure production engineering role
Culture Fit
Growth Potential
High
Salary Estimate
$180k-220k base (senior level with PhD premium)
Assessment Reasoning
FIT decision based on strong technical fundamentals (PhD in ML, 280+ citations), relevant production experience (3+ years at Zenith AI/Terminal Industries building ML systems), and demonstrated ability to lead technical teams and deliver business impact. While missing some specific MLOps tooling experience, the candidate shows exceptional learning ability, strong Python/PyTorch skills, and experience with core requirements. The combination of research depth and production experience is rare and valuable for a senior role requiring both technical rigor and practical engineering skills.
Interview Focus Areas
Experience Overview
7y total · 5y relevantExceptional ML researcher and engineer with 7+ years experience spanning academia and industry. Strong technical depth in modern ML systems, proven ability to ship production models, and demonstrated leadership in building ML teams from the ground up.
Matching Skills
Skills to Verify