Hiring for Senior Machine Learning Engineer :: Atlanta, GA :: Onsite

  • Atlanta, GA
  • Posted 20 hours ago | Updated 20 hours ago

Overview

On Site
Depends on Experience
Full Time

Skills

MLOPS; MACHINE LEARNING;

Job Details

Senior Machine Learning Engineer

Atlanta, GA

Job Description

Job Title: Senior Machine Learning Engineer

Role Summary

Leads the design, development, and scaling of end-to-end ML systems with a focus on automation, governance, and performance optimization. Architects MLOps platforms for model versioning, drift detection, and deployment orchestration across cloud environments. Ensures data quality, cost efficiency, and regulatory compliance while mentoring teams and driving best practices in production ML engineering.

Key Responsibilities

  • Design, develop, and deploy end-to-end ML pipelines, from data ingestion to production deployment, ensuring scalability and reproducibility.
  • Work closely with MLOps engineers to automate model training, validation, and deployment using CI/CD practices.
  • Optimize model performance, latency, and inference costs in production environments.
  • Collaborate with data scientists to convert experimental models into efficient, production-ready systems.
  • Implement model monitoring, drift detection, and retraining strategies for continuous improvement.
  • Ensure compliance with data governance, privacy, and security standards.
  • Develop reusable components, feature stores, and APIs for consistent model integration.
  • Stay up-to-date with new ML algorithms, frameworks, and MLOps tools (e.g., Vertex AI, SageMaker, MLflow, Kubeflow).
  • Participate in technical reviews, provide mentorship to junior engineers, and drive innovation within the Feuji AI Labs ecosystem.

Qualifications

Experience:

  • 6 10 years of overall experience, with 4+ years in ML Engineering.
  • Strong Python and Bash scripting expertise.
  • Proven experience in designing and deploying ML models at scale.
  • Proficiency in ML algorithms (XGBoost, LightGBM, CatBoost) and frameworks (TensorFlow, PyTorch, Keras). Experience with feature stores, model serving, and ML orchestration tools. Excellent troubleshooting, performance tuning, and incident resolution skills.
  • Proven ability to lead and mentor ML engineering teams.
  • Familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, or Google Cloud Platform).
  • Expertise in data pipeline orchestration (Airflow, Prefect, or Kubeflow).
  • Experience with feature engineering, model versioning, and A/B testing.
  • Hands-on with Git, CI/CD, REST APIs, and API gateways.
  • Knowledge of SQL/NoSQL databases, data lakes, and vector databases.
  • Strong understanding of machine learning lifecycle management and observability.
  • Excellent communication, analytical thinking, and collaboration skills.

Nice-to-Have Skills

  • Experience with LLM fine-tuning, RAG (Retrieval-Augmented Generation), or Generative AI pipelines.
  • Familiarity with MCP (Model Context Protocol) and agent orchestration frameworks (LangChain, LangGraph, or Haystack).
  • Exposure to data governance frameworks and ML observability tools (e.g., Arize, EvidentlyAI).
  • Understanding of business use cases in FinTech, Healthcare, or Supply Chain analytics.

Education:

  • Bachelor s or Master s Degree in Computer Science, Artificial Intelligence, Data Science, or related discipline.

Should you be interested, please send me a copy of your resume in word format along with the following details ASAP.

Full Name:
Current Location:
Hourly rate on C2C/W2:
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Earliest Available date to start:
Date and times available to interview:

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