Remote ML Engineer | MLOps & AI Pipelines Architect

Tetra Tech; Vienna, Northern (VA, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Halvik Corp is seeking an experienced ML Engineer to design and productionize ML models using Databricks, MLflow, and AWS services. You will collaborate with data scientists and engineers to build scalable pipelines, deploy models, and monitor performance in a fast-paced government-focused environment.

The role emphasizes strong Python skills, deep knowledge of ML libraries, and a pragmatic approach to MLOps, containerized deployments, and feature engineering.

Qualifications

• 5+ years of experience in ML Engineering or Applied ML.
• Strong Python skills with ML libraries (scikit-learn, XGBoost, PyTorch, TF).
• Proficient with Databricks, MLflow, and PySpark.
• Solid understanding of model lifecycle and MLOps practices.
• Experience with AWS-based data infrastructure and DevOps practices.
• Demonstrated ability to productionize models and integrate with business systems.
• Strong math and statistics background relevant to ML/AI.
• Experience with ML models (supervised, unsupervised, deep learning, etc.).
• Software engineering principles and best practices.
• Hands-on with training frameworks (TensorFlow, PyTorch, Hugging Face).
• Experience with MLOps tools on AWS (SageMaker, Lambda, S3).
• Practical experience with LLMs, RAGs, and AI agents.
• Databricks expertise for data engineering and ML pipelines.
• Advanced Python programming skills.
• Excellent communication and teamwork abilities.

Responsibilities

• Collaborate with data scientists and SMEs to develop ML models using curated datasets.
• Conduct experiments, prototypes, and proofs-of-concepts to validate model performance.
• Create scalable and reusable training pipelines using Databricks notebooks and MLflow.
• Implement LLMs, RAGs, and AI agent systems for business applications; CI/CD workflows.
• Operationalize models with robust CI/CD and deployment pipelines.
• Deploy models using MLflow, SageMaker, or custom APIs and monitor performance.
• Monitor production models for accuracy, drift, and latency; manage retraining schedules.
• Collaborate with Data Engineering to align ML pipelines with Medallion Architecture.
• Engineer high-quality features and maintain training/inference pipelines.

Skills

Python programming

ML libraries

Databricks

MLflow

PySpark

MLOps

AWS

Model deployment

Communication & teamwork

Tools

SageMaker

Lambda

S3

Streamlit

Databricks (tool)

TensorFlow

PyTorch

Hugging Face

Job description

Halvik Corp is seeking an experienced ML Engineer to design and productionize ML models using Databricks, MLflow, and AWS services. You will collaborate with data scientists and engineers to build scalable pipelines, deploy models, and monitor performance in a fast-paced government-focused environment.

The role emphasizes strong Python skills, deep knowledge of ML libraries, and a pragmatic approach to MLOps, containerized deployments, and feature engineering.