Machine Learning Engineer

Job description

Machine Learning EngineerRemote – PolandJR012487



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.



**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.



**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



JR012487

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