Machine Learning Engineer

Speria; Dunwoody (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Speria MTech in Atlanta seeks a highly skilled Machine Learning Engineer to design, build, and deploy scalable ML and optimization systems that drive real-time decision making across production workflows.

The role spans data processing, feature engineering, model development, and production deployment, with emphasis on Python, Spark, Databricks, and CI/CD. Collaboration with data engineering and a service-minded approach are essential.

Qualifications

• Bachelor's or Master's in a relevant field; MS may qualify with 1–2 years; BS typically 4–6 years
• 2–4 years experience in Machine Learning or optimization
• Experience deploying ML systems in production
• Familiarity with ML flow, Databricks, CI/CD
• Strong Python programming (production-level)
• Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)

Responsibilities

• Design and build machine learning and optimization pipelines
• Develop and deploy production-grade models
• Build feature pipelines using distributed systems (e.g., Spark)
• Collaborate with data engineering on data readiness
• Develop decisioning systems for automated actions
• Monitor model performance and improve continuously

Skills

Machine learning

Optimization

Python programming

Production deployment

Team collaboration

Education

Bachelor’s or Master’s degree in a relevant field

Tools

Databricks

Apache Spark

CI/CD

Job description

At Speria MTech, our company mission is to increase yield in protein production to help feed the growing world population without compromising animal welfare or damaging the planet. We aim to create software that delivers real-time data to the entire supply chain that allows producers to get better insight into what is happening on their farms and what they can do to responsibly improve production. Speria MTech is the industry-leading provider for Live Animal Protein Production Performance Management Tools. For over 30 years, Speria MTech has provided cutting-edge enterprise data solutions for all aspects of the live poultry operations cycle. We provide our customers with solutions in Business Intelligence, Live Production Accounting, Production Planning, and Remote Data Management—all through an integrated system. Our applications can currently be found running businesses on six continents in over 50 countries. Speria MTech has built an international reputation for equipping our customers with the power to utilize comprehensive data to maximize profitability. With over 300 employees globally, Speria MTech currently has main offices in Mexico, United States, and Brazil, with additional resources in key markets around the world. Speria MTech’s headquarters is based in Atlanta, Georgia and has approximately 90 team members in a casual, collaborative environment. Our work culture here is based on a passion for helping our clients feed the world, resulting in a flexible and rewarding atmosphere. We pride ourselves for having a working atmosphere that encourages collaboration, exceptional development tooling, training, and ongoing opportunities to work with senior and executive management.

About the Role

We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team at Speria MTech. The ideal candidate will play a crucial role in designing, building, and deploying scalable machine learning and optimization systems that drive real-time decision-making. The role spans data processing, feature engineering, model development, optimization modeling, and production deployment, contributing to systems that transform operational data into predictions and automated actions. We seek a solution-oriented individual who can provide answers rather than just identify problems. Embracing continuous change is key, as innovation and improvement are integral to Speria MTech's culture. This person should have a service-minded attitude, demonstrating a passion for enhancing the work of others and simplifying processes for stakeholders.

Responsibilities

• Design and build machine learning and optimization pipelines
• Develop and deploy production-grade models
• Build feature pipelines using distributed systems (e.g., Spark)
• Collaborate with data engineering on data readiness
• Develop decisioning systems for automated actions
• Monitor model performance and improve continuously

Qualifications

• Bachelor’s or Master’s degree in relevant field (MS may qualify with 1–2 years; BS typically 4–6 years)
• 2–4 years experience in Machine Learning or optimization
• Experience deploying Machine Learning systems in production
• Familiarity with Machine Learning flow, Databricks, CI/CD
• Strong Python programming (production-level)
• Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)

Preferred Skills

• SQL and Apache Spark experience
• Feature engineering pipelines for Machine Learning
• Experience with real-time systems
• Familiarity with LLMs, generative AI, and agent-based systems
• MS may qualify with 1–2 years; BS typically 4–6 years

MUST BE LOCATED IN ATLANTA AND BE ABLE TO COME INTO THE OFFICE AT LEAST 2 DAYS A WEEK