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HPE - MLOps Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Mid-level (2-5 years)

Work from:

Bulgaria

Offer summary

Qualifications:

Master's Degree in Computer Science or related field, 4+ years of relevant experience, Experience with ML pipelines in production systems, Knowledge of MLOps frameworks like Kubeflow, MLFlow, Proficiency in Python, Go, and shell script.

Key responsabilities:

Design and deploy MLOps frameworks and tools
Assist in technical design meeting customer needs
Integrate AI into business processes for customers
Provide consulting during project presales discussions
Manage small projects within the team

NATEK SME https://natek.eu/

501 - 1000 Employees

See more NATEK offers

Job description

Job Description

As an MLOps Engineer, you will be responsible for the design, development, integration and deployment of frameworks, tools and pipelines required for the end-to-end machine learning lifecycle in customer projects.

You will apply MLOps technologies to operationalize AI solutions at scale, integrated with client’s business processes and applications. You will be responsible for providing technical contribution and/or leadership in the creation and delivery of MLOps solutions designed to meet customers’ business needs and drive outcomes for the customers.

Your Responsibilities

Responsible for delivery of assigned tasks within the project lifecycle
Understand the company's technology portfolio and deliver technical design that meets customer requirements
Works with large scale computing frameworks, data analysis systems, and modeling environments
Applies MLOps methods and technologies to embed/integrate AI and analytic models into enhanced large-scale business processes and operational systems
Influences a client's strategic decisions by using deep industry expertise and deploying innovative MLOps and AI solutions in the operational systems
Provide technical consulting during project presales discussions
Resolve technical issues independently within your technical area
Work with team members to solution cross-technology assignments or address complex technical issues
Balance internal needs with customer needs within defined parameters
May identify additional services that could lead to future service revenue growth
Manage smaller projects/programs in the team
Participates as part of a team in developing and growing good relationships with team members and customers in assigned projects
Participate in technical or professional community events

Our Requirements

Master´s Degree in Computer Science, Engineering or related field and 4+ years of relevant experience
Experience in designing and implementing ML pipelines in production systems, including data preparation, model training, evaluation, monitoring and inference at scale
Knowledge of MLOps Frameworks, such as Kubeflow, MLFlow, Airflow, etc.
Experience with Linux, containers, and container orchestration technologies (Kubernetes, Openshift)
Extensive knowledge of programming languages such as Python, Go and shell script
Expertise with deep learning frameworks such as PyTorch and TensorFlow
Understanding of software engineering methodologies and DevOps practices (CI/CD)
Understanding of infrastructure requirements and accelerators
Ability to integrate technical knowledge and business understanding to create solutions for customers

Benefits

Fully remote work
Internal Mobility Program – enjoy many opportunities for career growth, job rotations, diversity of projects & technologies
Referral Program – enjoy cooperation with your colleagues and get a bonus!
5/10 Years NATEK Club – we offer long-term cooperation and celebrate each fifth-year cooperation anniversary with gifts
NATEK CSR Events & team buildings – enjoy our values: accountability, partnership and expertise and #workITwithus
Education – benefit from our know-how, learning courses and certificates and IT events – be part of the community of leaders of the industry and take part as a speaker or a visitor
Multisport
Technical and Personal training
Language courses

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