About Ensono
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.
Developing impactful solutions is something we do together at Ensono because Ideas Start Here. Great things happen when many voices are heard, and people are supported to run with their ideas. On our teams, you will be backed by leaders with a passion for our business. This is a place where your ideas can Do Great Things.
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.
Adventure starts here. Here you will be a part of a team that encourages you to master your craft, ask tomorrow’s questions today, and chart your path. Our Associates focus on client impact with curiosity and a feeling of relentless commitment.
About the role and what you will be doing
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.
Key Responsibilities
- 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.
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.
Benefits
We believe that great work deserves great rewards. In return for your ideas, commitment and ambition, we’ll give you a very competitive base salary and a range of benefits as soon as you join. On top of your highly competitive base salary, we offer:
- Flexible and remote work opportunities
- Performance bonus
- Training and development programs
- Worldwide career opportunities
- Community outreach and mentoring opportunities
- Learning platforms
- My Benefit system
- Wellness Platform support from Virgin Pulse
- Associate equity program
- Life insurance
- Lunch card
- Study leave
- One paid day off for charity events
- Sabbatical
- Extended parental leave
- Rental or co-financing of office equipment
- Referral bonus program
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.
