Machine Learning Engineer

Machine Learning Engineer  

At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.  

We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose.  

HONESTY, RELIABILITY, COLLABORATION, CURIOSITY, PASSION 

At Ensono, we're transforming into a software-first Managed Services Provider, where AI/ML and automation move us from reactive firefighting to predictive, zero-touch operations. Our Envision Operating System is the platform that makes this shift possible—bringing together data, intelligence, and automation across mainframe, distributed, and cloud environments. 

As a Machine Learning Engineer (ML Engineer), you'll be the builder who takes models from notebooks to production systems. You'll work side-by-side with Data Scientists to translate their predictive insights into scalable, high-performance solutions that can run reliably at enterprise scale. 

This is a role for makers—people who thrive at the intersection of code, models, and operations. You'll design APIs, deploy services, and ensure our AI capabilities integrate seamlessly with systems like ServiceNow, Snowflake, and Envision. Your work ensures that incident predictions, anomaly detections, and optimization recommendations don't just exist in theory—they power real-time operations, reduce downtime, and drive measurable business outcomes for our clients. 

If you're the kind of engineer who loves making AI actually work in production and want to be part of the team that's rewiring managed services with intelligent automation, this role is for you. 

What You Will Do: 

Model Deployment – Productionize machine learning models built by Data Scientists, ensuring they run reliably, securely, and at scale. 

API & Service Development – Design APIs and services that expose model predictions to EnvisionOS, ServiceNow, and other enterprise systems. 

Performance Optimization – Tune models for latency, throughput, and cost efficiency in real-time environments. 

Feature Pipeline Integration – Collaborate with Data Engineers to ensure robust feature pipelines feed models consistently and with minimal drift. 

Automation & Scaling – Use containers, orchestration, and CI/CD practices to automate deployment and monitoring of models. 

Cross-functional Collaboration – Work with Ops, Data Science, and MLOps to ensure models deliver actionable, explainable outcomes that drive trust and adoption. 

We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply.   

Required Skills & Experience 

Strong programming skills in Python (must-have) plus C, C++, Java, Javascript for performance-critical applications. 

Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. 

Hands-on experience with Docker, Kubernetes, or other container orchestration tools. 

Familiarity with Snowflake and data engineering workflows for integrating feature pipelines. 

Experience deploying models in production and exposing them through REST APIs, Flask, or Streamlit. 

Knowledge of SnowFlake is beneficial 

Strong understanding of model optimization, hyperparameter tuning, and inference performance. 

Experience working with ServiceNow or IT operations datasets is highly desirable. 

Mindset & Values 

Get Stuff Done – You take pride in moving models out of slides and into production. 

Builder at Heart – You see APIs, services, and pipelines as products that should be reliable, elegant, and scalable. 

Impact-Oriented – You measure success by uptime improvements, cost savings, and real-world adoption of AI-driven workflows. 

Collaborative Engineer – You bridge the gap between Data Scientists and Ops teams, speaking both "ML" and "production." 

Continuous Improver – Always looking for ways to make models faster, cheaper, and more accurate. 

Success Looks Like 

Models running in production pipelines, integrated with ServiceNow and EnvisionOS. 

Predictions that Ops teams trust and act on, reducing downtime and improving MTTR. 

Automated deployment workflows that keep models fresh, monitored, and reliable. 

AI capabilities that scale across mainframe, distributed, and cloud infrastructure seamlessly. 

Why Ensono? 

Ensono is a place where we unleash Associates to Do Great Things – for our clients and for your career. This could mean achieving a professional goal, collaborating with your team on an innovative idea, learning a new skill, reaching a wellness milestone, or engaging in your community through volunteer programs. Whatever it means to you, we want Ensono to be the place where you can do great things. 

We value flexibility and work-life balance. Positions that are not required to be onsite to support a client may offer the ability to work remotely or hybrid at an Ensono office location.