Full Stack Python Engineer

Full Stack Python Engineer

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward!

Key Responsibilities:

• Set technical direction for an 8–10 person engineering team.
• Serve as primary architect and code-quality gatekeeper (review/merge all GitHub PRs).
• Define and enforce standards for architecture, performance, testing, documentation, and CI/CD.
• Own the end-to-end codebase for a distributed forecasting platform built on Python and Apache Spark (GCP).
• Champion and evolve the internal ML tooling library used for training, evaluation, metrics, and visualization.

Forecasting Platform Development

• Build and maintain scalable data pipelines and feature engineering workflows for intermittent and lumpy MRO/spare‑parts demand.
• Extend and improve metrics instrumentation (sMAPE, MASE, Dollar‑Weighted MAE, bias, diagnostics).
• Support multi-model training, evaluation, selection, calibration, and DFU lifecycle management.
• Integrate and maintain MLflow for experiment tracking, model registry, and reproducibility.
• Convert research prototypes into high-quality, production-grade components within the shared library.

Blue Yonder Integration

• Act as the technical interface between the ML Forecasting Factory and Blue Yonder workflows.
• Ensure forecast outputs, calibration parameters, and hierarchy-level signals align with Blue Yonder's format and multi-model framework.
• Collaborate with planning stakeholders to maintain compatibility with proportional allocation logic and DFU lifecycle behavior.

Team Leadership & Collaboration

• Provide mentorship, technical guidance, and architectural leadership to engineering teammates.
• Translate business needs into engineering specs in partnership with data scientists.
• Operate as a hands-on contributor with daily codebase involvement.

Here is what you need:

• US citizenship (Secret eligibility)
• BS degree
• 5+ years of professional production Python engineering experience.
• Experience building or maintaining shared internal Python libraries or ML tooling packages.
• Strong proficiency with Pandas, NumPy, and scikit-learn.
• Proven Staff/Principal-level technical leadership with architectural ownership and PR-based code stewardship.
• Experience with large-scale distributed data processing using Apache Spark.
• Hands-on experience with GCP services such as Dataproc, BigQuery, and GCS.
• Strong Git/GitHub fluency (branching, PR workflows, release management).
• Ability to mentor and lead engineers and PMs with clarity and technical credibility.

Preferred experience:

• Active DoD Secret clearance highly desired
• ML engineering background including training pipelines, evaluation frameworks, MLflow, and deployment patterns.
• Production or near-production experience with TensorFlow and/or PyTorch.
• Experience with forecasting/time-series libraries such as sktime or AutoGluon.
• Familiarity with Blue Yonder (JDA) or similar enterprise planning platforms, especially multi-model forecasting and DFU management.