Senior AI/ML Engineer

Job Category:
AI/ML
Job Type:
Hybrid
Job Location:
Indiana Indianapolis
Compensation:
Depends on Experience
W2:
W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.
Job Description
US Work Authorization Requirement:
Candidates must be legally authorized to work in the United States without employer sponsorship. This includes, but is not limited to, U.S. Citizens, Permanent Residents, and other individuals with valid U.S. work authorization.
**Job Description:**
We are seeking a highly skilled
Senior AI/ML Engineer
with 8+ years of experience in artificial intelligence, machine learning, and production-grade software engineering. This role serves as a critical bridge between cutting-edge research and scalable enterprise solutions.
The ideal candidate will own the full AI lifecycle—from architecting advanced neural networks and fine-tuning Large Language Models (LLMs) to building robust MLOps pipelines and enabling scalable AI platforms within Databricks. As a senior technical leader, you will champion engineering best practices, mentor junior engineers, and translate complex business challenges into impactful AI-driven applications.
**Key Responsibilities:**

• Design, develop, and deploy scalable ML models including regression, forecasting, and deep learning architectures.
• Lead LLM integration and fine-tuning using techniques like LoRA and PEFT while optimizing performance and cost.
• Build and automate MLOps pipelines in Databricks using Docker, FastAPI, and serverless solutions.
• Develop user-facing AI tools and ensure seamless system integration.
• Maintain data quality, infrastructure reliability, and platform scalability.
• Mentor junior engineers and collaborate with cross-functional teams to drive AI adoption.

**Technical Qualifications**

• 8+ years of experience in AI/ML engineering and software development.
• Advanced Python expertise including pandas, polars, NumPy, scikit-learn, and PyTorch.
• Strong hands-on experience with Generative AI, prompt engineering, and LLM fine-tuning.
• Experience evaluating model performance, latency, and scalability.
• Hands-on experience with AWS or Azure cloud platforms.
• Strong understanding of Git, Docker, CI/CD, and modern development workflows.
• Expertise in data cleaning, feature engineering, and visualization (e.g., Seaborn).
• Deep knowledge of Databricks including AutoML and model lifecycle automation.
• Experience building APIs using FastAPI and deploying scalable AI solutions.

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