Simelabs - Python ML Engineer
Astek
Key Responsibilities :1. Incident Management & Bug Fixing :- Investigate and resolve incidents reported on AI algorithms (model crashes, wrong outputs, data pipeline failures, performance degradation).- Diagnose root causes: data issues, code bugs, dependency conflicts, model drift.- Apply fixes, test and validate corrections before redeployment.- Document incidents and resolutions in the ticketing system.2. Algorithm Maintenance :- Apply patches, dependency updates and environment fixes.- Ensure models remain functional after infrastructure changes (cloud updates, library upgrades, data schema changes).- Maintain and update data preprocessing pipelines feeding the models.3. Code Review & Quality :- Read, understand and improve existing Python codebases (often written by Data Scientists).- Refactor poorly structured code to improve maintainability and reliability.Experience : - 3+ years of experience.Core Technical Skills :- Python: Advanced Python, debugging, OOP, clean code (Expert).- Data manipulation: Pandas, NumPy, data wrangling, ETL pipelines (Intermediate).- ML Frameworks: Scikit-learn, TensorFlow or PyTorch (reading & fixing, not training from scratch) (Intermediate).- API & services: FastAPI, REST APIs, JSON, basic microservices (Intermediate).- Version control: Git + GitHub (Advanced) (Intermediate).- Environment management: Poetry, pip, virtual environments, requirements management (Expert).- Cloud - GCP AI Services: GCP Projects, Vertex AI, BigQuery, Service Account, Google Storage (Buckets), Artifact Registry (Beginner).- Containerisation: Docker - run, build, debug a container (Intermediate).- SQL: Ability to query databases and investigate data issues (Intermediate).GitHub - Advanced Skills:- The consultant must demonstrate advanced proficiency with GitHub beyond basic commit/push usage, including:1. Repository & Code Management: Branching strategies (GitFlow, trunk-based development, feature branches), Pull Request lifecycle (creating, reviewing, requesting changes, approving and merging), Resolving merge conflicts confidently on complex Python codebases, Tagging, releases and semantic versioning.2. Collaboration & Governance: Branch protection rules (required reviews, status checks before merge), Code review best practices (inline comments, suggesting changes directly in PRs).3. Advanced Features: GitHub Packages (publishing and consuming internal Python packages), Pre-commit hooks and linting integration (Black, Flake8, isort), Git history investigation (git bisect, git blame, git log - graph to trace the origin of a bug). (ref:hirist.tech)
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