- Company Name
- Nike
- Job Title
- Senior AI/ML Engineer
- Job Description
-
Job title: Senior AI/ML Engineer
Role Summary:
Lead the design, implementation, and deployment of scalable machine learning and generative AI solutions for corporate functions. Use advanced analytics to drive data‑driven decision making and deliver measurable business impact.
Expactations:
- Drive end‑to‑end MLOps lifecycle from experimentation through production and monitoring.
- Provide technical leadership, mentorship, and code reviews.
- Collaborate with product owners, business stakeholders, and cross‑functional teams.
- Influence technical strategy and maintain best practices for reliability, security, and performance.
Key Responsibilities:
- Design and build production‑ready ML pipelines using AWS services (SageMaker, Lambda, ECR).
- Develop and deploy optimized models, prediction services, and optimization programs.
- Automate CI/CD workflows with Docker, Jenkins, Terraform, and GitHub Actions.
- Orchestrate data pipelines with Airflow or Databricks Workflows; extract, transform, and load large datasets.
- Mentor teammates in Python coding standards, TDD, and Agile practices.
- Collaborate with data engineering, infra, and product teams to resolve dependencies and integrate solutions.
- Evaluate new frameworks (PyTorch, TensorFlow, Spark) and tools for continuous improvement.
- Ensure models are secure, scalable, and comply with governance and data privacy policies.
Required Skills:
- 5–7 years of software engineering experience, 3+ years in ML Engineering.
- Strong Python programming, containerization, and CI/CD automation.
- Proficiency with Scikit‑learn, PyTorch, TensorFlow, Spark, FastAPI, or similar.
- Deep experience in AWS (SageMaker, Lambda, ECR, API Gateway).
- MLOps expertise: experimentation, model registry, deployment, monitoring, and A/B testing.
- Knowledge of data modeling, SQL, ETL pipelines, and data structures.
- Familiarity with Airflow, Databricks Workflows, Kubernetes, Docker, Jenkins, Terraform.
- Agile and test‑driven development mindset.
- Excellent communication, collaboration, and problem‑solving skills.
Required Education & Certifications:
- Bachelor’s degree in Computer Science or related field (or equivalent experience).
- Valid certifications in AWS (e.g., AWS Certified Machine Learning– Specialty) preferred.