[Remote] Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Allied Resources Technical Consultants 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 hands-on role involves developing AI/ML predictions, designing AI agent-based systems, and optimizing cloud data and ML infrastructure.

Responsibilities

• 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
• 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
• 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

Skills

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

Benefits

• Remote role
• Occasional travel required

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