Machine Learning Engineer

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.

Job Summary

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.

Essential Functions & Responsibilities

Essential responsibilities include and functions of the Machine Learning Engineer are:

• 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, Skills, And Experience

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
• Git, CI/CD, reproducible workflows
• 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

Speria delivers operational intelligence solutions for food systems, helping producers and integrators improve efficiency, build predictability and enable greater productivity. This means improving feed conversion, reducing waste and emissions, and supporting animal health and welfare.