Director of Machine Learning

6y relevant experience

Under Review

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

This candidate is a technically credible senior data scientist with ~11 years of ML engineering experience, strong NLP/LLM credentials from JPMorgan, and a solid academic background. However, this is fundamentally an individual contributor profile being evaluated against a Director-level role that requires proven team leadership, strategic roadmap ownership, and organizational influence — none of which are evidenced in the application. The most pressing issue is the LinkedIn URL resolving to a completely different person, which must be resolved immediately as it undermines overall application credibility. If the identity concern is satisfactorily resolved and the candidate can demonstrate any leadership trajectory, they could be a strong senior IC hire or a stretch candidate for a Lead ML Engineer role, but are not currently demonstrating readiness for the Director position as specified.

Top Strengths

✓Deep hands-on ML/NLP engineering experience at credible institutions (JPMorgan, Airbus, IBM)
✓Production LLM customization and deployment in regulated financial environment
✓Strong academic foundation: MSc CS + AI PG Diploma from University of Exeter
✓Multi-cloud deployment experience (AWS and GCP) with real production workloads
✓Research publications and patents demonstrating technical depth beyond typical practitioner

Key Concerns

!LinkedIn profile mismatch is a critical red flag that must be resolved — the profile links to a completely unrelated person in procurement
!Zero evidence of team leadership, people management, or Director-level responsibilities — the role's primary requirement

Culture Fit

48%

Growth Potential

Moderate

Salary Estimate

$90k-$120k (aligned with Senior/Staff IC Data Scientist, below Director band of $130k-$180k)

Assessment Reasoning

Scored BORDERLINE (52/100) rather than NOT_FIT because the candidate's technical ML credentials are genuinely strong — JPMorgan production LLM work, multi-cloud deployment, and a diverse ML portfolio are real signals of a capable senior practitioner. However, the score is held below FIT threshold for three key reasons: (1) complete absence of team leadership or management experience, which is the defining competency for a Director role; (2) the LinkedIn URL submits to a different person entirely, creating an unresolved identity/integrity concern that must be clarified before any process advancement; and (3) no evidence of ML strategy, roadmap definition, or cross-functional leadership. The candidate may be a strong fit for a Senior ML Engineer or Staff Data Scientist role but has not demonstrated Director-level readiness. Recommend holding advancement pending LinkedIn clarification, then reassessing for a potential senior IC track if resolved positively.

Interview Focus Areas

Clarify LinkedIn URL discrepancy and verify identity/profile ownership before proceedingProbe for any informal leadership, mentoring, or team coordination experience not captured in resumeAssess ML system architecture thinking — can they design end-to-end pipelines vs. implement components?Evaluate strategic thinking: how would they translate business recruiting problems into an ML roadmap?Explore familiarity with MLOps tooling and production model governance at scale

Code Review

FairSenior Level

No GitHub profile or code samples were provided, making direct code quality assessment impossible. Based on resume claims alone, the candidate appears to be a senior-level ML practitioner capable of production deployment, but Principal or Director-level architectural judgment cannot be confirmed without code evidence. The absence of any public technical presence limits confidence in this dimension significantly.

+Technical breadth implied by publications and patents in ML/distributed systems
+Multi-cloud deployment experience suggests production engineering capability

-No GitHub profile provided — no verifiable code artifacts to assess
-Cannot evaluate coding standards, architecture patterns, or open-source contributions
-No demonstration of ML system design documentation or architecture outputs

Experience Overview

11y total · 6y relevant

Deepak Jha presents as a technically capable individual contributor data scientist with solid ML/NLP credentials built across JPMorgan, Airbus, and IBM over ~11 years. However, the role demands Director-level leadership — managing teams of 4-6, defining ML strategy, and owning roadmaps — for which there is no demonstrable evidence in this resume. The LinkedIn profile mismatch is a significant red flag requiring immediate clarification.

Matching Skills

Machine Learning EngineeringDeep LearningPython (implied via ML work)LLMs & Transformers (customized LLM at JPMorgan)Model Deployment (multi-cloud AWS/GCP)NLP & Text GenerationComputer VisionAWS (Lambda, cloud deployment)

Skills to Verify

Team Leadership / ML Team Management (no evidence of managing engineers)ML Systems Design at architectural scaleMLOps tooling (MLflow, Weights & Biases, Airflow, Dagster)Model performance optimization for B2B SaaSDirector-level strategy and roadmap ownershipKubernetes / Docker (not mentioned)Scikit-learn / PyTorch / TensorFlow explicitly listedData Pipeline Architecture at enterprise scale

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