Machine Learning Engineer
Company: Gravity IT Resources
Location: Nashville
Posted on: November 26, 2025
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Job Description:
Job Description Machine Learning Engineer Employment Type:
Full-Time Location: Nashville, TN (hybrid) About the Role We’re
hiring a Maching Learning Engineer to design and deploy AI systems
end-to-end — from data preparation and evaluation to model
fine-tuning, inference, and agentic workflows. You’ll work closely
with product and engineering teams to deliver reliable,
cost-effective, and scalable LLM-powered solutions on AWS. What
You’ll Do End-to-End GenAI Solutions: Scope problems, choose the
right approach (prompt engineering, fine-tuning, agents),
implement, evaluate, and deploy. Data & SQL: Write efficient SQL
for analytics and data prep; manage schemas and pipelines for model
training and inference. Model Training & Fine-Tuning: Run
supervised fine-tuning (PEFT/LoRA/QLoRA), optimize prompts, and
manage experiment tracking/evaluation. Agentic Systems: Build agent
workflows with tool use, memory, and safety/guardrails. Inference &
Deployment: Package services with Docker, optimize latency and cost
(batching, caching, quantization), and deploy on AWS (ECS, EKS,
SageMaker, Lambda with GPU acceleration). MLOps & Observability:
Set up CI/CD for models/prompts; maintain offline/online evaluation
pipelines, monitoring, and rollback strategies. Security &
Compliance: Implement data governance, PHI/PII protections, and
guardrails against prompt injection and unsafe outputs.
Cross-Functional Collaboration: Work with product managers and
engineers to align GenAI capabilities with product goals; clearly
document and communicate trade-offs. Production Readiness: Lead
conversations around scaling, monitoring, and maintaining GenAI
systems in production environments. Minimum Qualifications 5 years
of Software/ML engineering experience, including 2 years building
and deploying GenAI/LLM systems. MS/PhD in Computer Science, Data
Science, or equivalent experience. Strong SQL and Python skills
with solid software engineering fundamentals. Experience with agent
frameworks (LangGraph, AutoGen, CrewAI) and tool-driven agents.
Hands-on with deep learning (PyTorch or TensorFlow) and LLM
fine-tuning (SFT/PEFT like LoRA/QLoRA). Production experience with
Docker and AWS (ECS, EKS, SageMaker, Lambda, or GPU services).
Experience building scalable data and model pipelines for training
and deployment. Familiarity with prompt engineering, evaluation
frameworks (LLM-as-judge, metrics), and offline test harnesses.
Understanding of security & compliance for sensitive data (e.g.,
PHI/PII). Excellent problem-solving, communication, and
documentation skills. Preferred Qualifications Experience with
inference optimization: quantization (bitsandbytes, GPTQ/AWQ),
batching, caching, or vLLM. Background in healthcare, including
HIPAA compliance or medical data handling. Experience with
experiment tracking (MLflow, W&B), CI/CD for ML, and monitoring
tools (Prometheus, Grafana). Familiarity with major LLM APIs and
open-source models (OpenAI, Anthropic, Llama, Mistral). Tech Stack
Languages: Python, SQL DL/LLM: PyTorch, TensorFlow, Hugging Face,
PEFT/TRL, vLLM Data: Snowflake, Postgres Cloud: AWS (ECS, EKS,
SageMaker, Lambda) MLOps: Docker, CI/CD, MLflow, or W&B
Keywords: Gravity IT Resources, Shreveport , Machine Learning Engineer, Engineering , Nashville, Louisiana
