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.

Machine Learning Engineer

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