Machine Learning Engineer

Our client is seeking a Machine Learning Engineer to take ownership of building and scaling the data and ML infrastructure that powers their AI‑driven products. This is a hands‑on, high‑impact role for someone who understands that great AI starts with great data engineering and extends into AI agents and applied machine learning solutions.

This is a remote role, with occasional travel required.

What You’ll Do:

Engineering, AI Agents & Applied ML:

• Own the development of trusted AI/ML predictions, AI agents, and applied machine learning solutions, including feature pipelines, model input/output data flows, and robust data validation frameworks
• Design, build, and deploy AI agent-based systems that integrate with production environments
• Implement scalable and reliable machine learning pipelines supporting both experimentation and real-world applications
• Design and implement reliable, scalable, and secure data pipelines for analytical and product use cases
• Provide technical leadership and mentorship to engineers and cross‑functional partners, fostering a culture of engineering excellence

Ecosystem Ownership & Strategy:

• Own the architecture and evolution of the data and ML platform, ensuring it supports AI agents and production ML workloads
• Implement data governance, quality, and observability best practices, proactively managing data health
• Optimize cloud data and ML infrastructure for cost, performance, and scalability, treating the platform as a product

Collaboration & Business Translation:

• Partner closely with product managers, engineers, and stakeholders to deliver AI-driven and agent-based solutions
• Translate business requirements into scalable applied machine learning systems
• Ensure all ML and AI initiatives deliver measurable business value and strong user outcomes

What You’ll Bring

Experience:

• 5+ years of experience in data engineering or machine learning engineering
• Experience building AI agents and applied machine learning solutions in production environments
• 1–2+ years in a senior or lead capacity

Technical Expertise:

• Deep understanding of machine learning models and applied ML techniques, including trade-offs (accuracy vs. interpretability, complexity vs. performance)
• Strong experience developing and deploying AI agents or agent-based architectures
• Advanced Python skills for data processing, automation, and ML pipeline development
• Strong SQL expertise

ML, AI Agents & MLOps:

• Experience with Scikit-learn and similar ML libraries
• Hands-on experience building and maintaining feature engineering pipelines and applied ML workflows
• Experience designing, deploying, or integrating AI agents (e.g., LLM-based or autonomous workflows)
• Strong proficiency with MLOps tools such as Airflow, dbt, or Dagster

Modern Data Stack:

• Experience with Snowflake, BigQuery, Redshift, or Databricks
• Strong understanding of data modeling, performance optimization, and cloud platforms (AWS, GCP, or Azure)

Additional Info:

• Remote role with occasional travel required

EEO Policy

Allied Resources complies with all Equal Employment Opportunity (EEO) affirmative action laws and regulations and does not discriminate based on protected characteristics.