Senior ML Engineer

6y relevant experience

Qualified

For hiring agencies & HR teams

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

Strong ML engineer with diverse production experience and proven business impact. Technical skills align well with core requirements, particularly in Python, PyTorch, and cloud platforms. Leadership experience and recent GenAI work are valuable assets. Main gap is in MLOps infrastructure (Kubernetes, monitoring), but strong fundamentals suggest quick ramp-up potential. Location logistics need clarification for hybrid Austin role.

Top Strengths

✓7+ years ML experience with production deployments
✓Cross-domain expertise: CV, NLP, time series, GenAI
✓Team leadership experience managing ML teams
✓Recent experience with cutting-edge technologies (RAG, GraphRAG, LLMs)
✓Strong business impact track record (95% accuracy invoice processing, doubled wind turbine restart rates)

Key Concerns

!MLOps infrastructure gap (no Kubernetes, limited CI/CD pipeline experience)
!Location in Spain may complicate Austin-based hybrid role

Culture Fit

72%

Growth Potential

High

Salary Estimate

$140k-170k (accounting for relocation from Spain)

Assessment Reasoning

FIT decision based on strong technical foundation (7+ years ML experience), proven production deployment track record across multiple companies, and demonstrated business impact. While missing some MLOps infrastructure experience (Kubernetes, formal monitoring tools), the candidate's core ML engineering skills, leadership experience, and recent cutting-edge work with LLMs/RAG systems indicate strong potential. The 78/100 score reflects solid alignment with most requirements despite infrastructure gaps that could be addressed with onboarding.

Interview Focus Areas

MLOps and production infrastructure experienceKubernetes and container orchestrationModel monitoring and observability practicesWillingness to relocate or work US hours

Experience Overview

7y total · 6y relevant

Experienced ML practitioner with strong technical foundation and proven track record of delivering production ML systems. Has relevant experience but may need upskilling in MLOps infrastructure.

Matching Skills

PythonPyTorchTensorFlowAWSDockerSQL

Skills to Verify

KubernetesMLOps pipelinesMLflow/Kubeflow

Candidate information is anonymized. Personal details are hidden for fair evaluation.