Applied AI Researcher / Founding Engineer
6y 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
The candidate is a highly compelling candidate for the Applied AI Researcher / Founding Engineer role, presenting one of the strongest technical and academic profiles likely to be seen for this position. Their PhD (summa cum laude, award-winning), 400+ citation research output, current ML leadership at a funded startup, and hands-on expertise across the full AI/MLOps stack place them well above the minimum requirements. The entrepreneurial experience at ElevenEleven and the measurable business outcomes at Kitro demonstrate both the technical execution and leadership maturity needed for a founding engineer mandate. The two primary concerns — multiple concurrent commitments and the absence of code samples — are addressable through structured interviewing and should not preclude advancement. A prompt injection attempt embedded in the resume is noted as a flag for awareness but is not considered disqualifying. This candidate is strongly recommended for an expedited technical interview and executive alignment conversation.
Top Strengths
- ✓Award-winning PhD in Computer Science with 400+ citation research track record — top-tier academic foundation directly matching the role's preferred qualifications
- ✓Proven team leadership as Head of ML at a funded startup with demonstrable business impact (>100k€/month savings), directly relevant to the founding engineer mandate
- ✓Entrepreneurial DNA evidenced by co-founding ElevenEleven alongside a full-time senior role, signaling the high-ownership, fast-moving mindset the role demands
- ✓Exceptionally broad and deep technical stack spanning generative AI, LLMs, computer vision, MLOps, cloud infrastructure, and embedded systems — rare combination for a single engineer
- ✓Track record of delivering novel, production-grade AI systems in high-stakes domains (nuclear power plant inspection, food waste AI, energy forecasting) across multiple industries
Key Concerns
- !Multiple active professional commitments (Head of ML at Kitro, Founder at ElevenEleven, volunteer secretary) raise legitimate questions about bandwidth and full-time dedication to a founding role that demands complete focus
- !No code samples or GitHub profile provided, leaving engineering rigor and code quality unverified — critical gap for a role requiring ownership of the entire technical foundation
Culture Fit
Growth Potential
High
Salary Estimate
$90,000 - $130,000 (Croatia-based EU location may influence expectations; founding equity stake will likely be a key negotiation lever alongside base salary)
Assessment Reasoning
The candidate is assessed as FIT with a high overall score of 88/100. The decision is driven by an exceptionally strong alignment across virtually all critical dimensions of the role: (1) Academic credentials — PhD in Computer Science summa cum laude with an outstanding dissertation award directly satisfies the preferred qualification; (2) Technical skills — deep hands-on expertise in Python, PyTorch, LLMs, generative AI, computer vision, MLOps, AWS, and GCP covers 90%+ of required and preferred skills; (3) Leadership experience — current Head of ML role managing a team at a funded startup with demonstrated ROI exceeds the leadership potential requirement; (4) Delivery track record — world-first certified AI for nuclear inspection, food waste AI platform, published consumer app, and 400+ citation publications constitute a strong proof-of-delivery record; (5) Entrepreneurial mindset — founding ElevenEleven alongside senior employment signals the ownership orientation essential for a founding engineer. The score does not reach 95+ due to: absence of code samples (unverifiable engineering quality), no GitHub profile, multiple concurrent commitments requiring clarification, and minor LinkedIn incompleteness. None of these concerns constitute disqualifying red flags. The candidate comfortably exceeds the FIT threshold of 70 and is recommended to advance to the technical interview stage with priority.
Interview Focus Areas
Code Review
No direct code artifacts were submitted for review, preventing an objective assessment of code quality, style, and engineering best practices. Based on resume evidence alone — production AI systems in safety-critical environments, MLOps tooling proficiency, and open-source contributions — the candidate is strongly inferred to operate at a Senior to Principal engineering level. A technical interview or take-home challenge is strongly recommended to validate this inference.
- +Extensive technology stack cited across the resume (PyTorch, DVC, WandB, Docker, CUDA, Airflow, Voxel51, Flask, GitHub workflows) suggests broad practical engineering capability
- +Led development of world's first certified AI for nuclear power plant inspection, implying production-quality, safety-critical code standards
- -No code samples, GitHub profile, or open-source repositories were provided, making objective code quality assessment impossible
- -Score is penalized solely due to absence of evidence, not negative evidence — inferred seniority from resume context is high
Experience Overview
6y total · 6y relevantThe candidate presents an exceptionally strong profile for this role, combining a PhD in Computer Science (summa cum laude, award-winning dissertation), 6 years of directly relevant AI/ML experience, and current leadership of an ML department at a Zurich-based startup. Their hands-on expertise spans LLMs, generative models, computer vision, and MLOps, with measurable real-world business outcomes. The absence of a GitHub profile and the multiple concurrent commitments are the primary areas requiring clarification during the interview process.
Matching Skills
Skills to Verify