Applied ML Product Builder

About the role

Senior Applied Data Scientist / Machine Learning Engineer (Applied ML Product Builder) joining a growing team that builds intelligent, data‑driven products at scale, responsible for designing, deploying, and optimizing machine learning solutions that directly impact customers and business outcomes.

About the company

Allied Resources Technical Consultants (ARTC) is an engineering recruitment and consulting firm that provides talent and consulting services across industries such as renewables, electric utilities, public infrastructure, oil and gas, engineering, and life sciences. It is part of Allied Resources Group, a national network of specialized companies delivering integrated technical services in engineering, staffing, healthcare, inspection, and construction management.

Requirements

• 5+ years of experience in Applied Data Science, Machine Learning, AI, or ML Engineering.
• Proven experience building, deploying, and maintaining machine learning models in production environments.
• Strong programming skills in Python and advanced proficiency in SQL.
• Hands‑on experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit‑learn, XGBoost, or similar.
• Deep understanding of supervised learning, forecasting, recommendation systems, ranking algorithms, optimization techniques, statistical modeling, and experimentation frameworks.
• Experience working with large‑scale, real‑world datasets and solving complex product challenges.
• Strong background in data engineering concepts, feature engineering, and data pipelines.
• Experience partnering with software engineering teams to deploy, monitor, and improve production ML systems.
• Familiarity with modern data platforms such as Databricks, Snowflake, BigQuery, Redshift, or similar.
• Understanding of MLOps best practices including monitoring, model governance, feature stores, and automated retraining.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Strong product mindset with ability to connect ML initiatives to business objectives and customer outcomes.
• Excellent communication and stakeholder management skills.
• Experience building ML‑powered SaaS products (preferred).
• Experience with decision intelligence, workforce optimization, pricing, scheduling, route optimization, marketplace, or operational intelligence solutions (preferred).
• Experience with LLMs, Generative AI, Retrieval‑Augmented Generation (RAG), or agentic AI applications in production (preferred).
• Experience designing and analyzing A/B tests, experimentation platforms, or causal inference frameworks (preferred).
• Experience operating machine learning systems at scale with feedback loops and continuous improvement processes (preferred).
• Previous senior, staff, or lead data scientist, applied scientist, or machine learning engineer roles (preferred).