ML Ops Enigneer / 1 at Inetum

Warsaw, Masovian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

25 Feb, 26

Salary

0.0

Posted On

27 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ML Ops, Databricks, Infrastructure as Code, Terraform, ML Scoring, Job Scheduling, Monitoring, Security, Compliance, Automation, Collaboration, CI/CD, Data Science, Model Performance Monitoring, Logging, Alerting

Industry

IT Services and IT Consulting

Description

Company Description Inetum Polska is part of the global Inetum Group and plays a key role in driving the digital transformation of businesses and public institutions. Operating in cities such as Warsaw, Poznan, Katowice, Lublin, Rzeszow the company offers a wide range of IT services. Inetum Polska actively supports employee development by fully funding training, certifications, and participation in technology conferences. Additionally, the company is involved in local social initiatives, such as charitable projects and promoting an active lifestyle. It prides itself on fostering a diverse and inclusive work environment, ensuring equal opportunities for all. Globally, Inetum operates in 19 countries and employs over 28,000 professionals. The company focuses on four key areas: Consulting (Inetum Consulting): Strategic advisory services that help organizations define and implement innovative solutions. Infrastructure and Application Management (Inetum Technologies): Designing and managing IT systems tailored to clients’ individual needs. Software Implementation (Inetum Solutions): Deploying partner solutions from industry leaders like Microsoft, SAP, Salesforce, and ServiceNow. With strategic partnerships with major technology giants, including Microsoft, SAP, Salesforce, and ServiceNow, Inetum delivers advanced technological solutions tailored to customer requirements. In 2023, Inetum reported revenues of €2.5 billion, underscoring its strong position in the digital services market. Inetum distinguishes itself by offering a comprehensive range of benefits that meet the diverse needs of employees, providing flexibility, support and commitment. Here's what makes working at Inetum unique: Flexible and hybrid work: Flexible working hours. Hybrid work model, allowing employees to divide their time between home and modern offices in key Polish cities. Attractive financial benefits: A cafeteria system that allows employees to personalize benefits by choosing from a variety of options. Generous referral bonuses, offering up to PLN6,000 for referring specialists. Community and Well-Being: Dedicated team-building budget for online and on-site team events. Opportunities to participate in charitable initiatives and local sports programs. A supportive and inclusive work culture with an emphasis on diversity and mutual respect. Job Description We are seeking an advanced ML Ops Engineer to design and implement the infrastructure required to host, orchestrate, and manage up to 1,500 ML scoring processes within a new Databricks environment. The focus of the role is on operationalizing the ML scoring pipelines by setting up a scalable, secure, and well‑monitored platform for data science teams to deploy their models. Qualifications Environment Configuration Set up Databricks clusters, jobs, and workflows for large-scale ML scoring use cases. Infrastructure as Code is used for reproducibility and governance (e.g., Terraform). Implement scalable infrastructure capable of running thousands of ML scoring tasks. Configure job scheduling, parallel execution strategies, and resource optimization. Monitoring and alerting are integrated into the platform using cloud-native tools. Security, compliance, and cost-efficiency are key pillars of the operational setup. ML Ops Pipeline Integration Develop deployment processes for ML models using Databricks MLflow or equivalent. Implement version control and tracking for models, scoring code, and configuration files. Execution Management Build frameworks to orchestrate scoring of >1,500 ML models or scoring jobs. Ensure resilience, fault tolerance, and restart capabilities for failed jobs. Monitoring & Observability Integrate logging, alerting, and dashboards to monitor scoring throughput, latency, and failures. Establish model performance monitoring hooks for post‑scoring analytics. Automation Work alongside Dev Ops Engineers to ensure common infrastructure and processes (e.g., shared storage, Delta Lake tables) serve both ML and BI use cases. Automate provisioning of resources and deployments from CI/CD pipelines. Utilize Infrastructure as Code (IaC) where feasible for reproducibility. Collaboration Work closely with data scientists, solution architects, and platform engineers to ensure smooth handover from model development to operational scoring. Define operational SLAs for scoring workloads. Additional Information Work 3 times a week from an office in Warsaw, Lublin or Poznań.

Responsibilities

The ML Ops Engineer will design and implement the infrastructure for managing ML scoring processes within a Databricks environment. The role focuses on operationalizing ML pipelines and ensuring a scalable and secure platform for data science teams.