Sr ML Ops Engineer

Description

Join GlobalLogic, to be a valid part of the team working on a huge software project for the world-class company providing M2M / IoT 4G/5G modules e.g. to the automotive, healthcare and logistics industries. Through our engagement, we contribute to our customer in developing the end-user modules firmware, implementing new features, maintaining compatibility with the newest telecommunication and industry standards, as well as performing analysis and estimations of the customer requirements.

Requirements

Bachelor's, Master's, or Ph.D. degree in Computer Science, Data Science, Engineering, or a related field.

8+ years of experience in machine learning engineering or data science with a focus on building, deploying, and maintaining machine learning systems.

Strong proficiency in programming languages such as Python, R, or Java.

Extensive experience with ML frameworks such as Scikit-learn, TensorFlow, or similar.

Experience with NLP, RAGs, Agentic frameworks,or other advanced ML techniques.

Strong understanding of data structures, algorithms, and software engineering principles.

Hands-on experience with cloud platforms such as AWS, Google Cloud, or Azure for deploying ML models and managing infrastructure.

Proficiency in SQL and working with large datasets (e.g., in relational databases, NoSQL systems) .

Knowledge of model deployment, monitoring, and optimization in a production environment.

Excellent problem-solving skills, analytical thinking, and attention to detail.

Strong communication skills, with the ability to explain complex ML concepts to non-technical stakeholders.

Preferred Qualifications:

Experience with Snowflake

Familiarity with MLOps tools and practices for automating and managing ML workflows.

Knowledge of data privacy regulations (e.g., GDPR) and best practices for handling sensitive data.

Contributions to the open-source community or publications in relevant journals.

Job responsibilities

About Role:

As a Senior ML Engineer, you will be responsible for designing, developing, and deploying state-of-the-art machine learning models and algorithms that drive innovation in our products. You will work closely with data scientists, software engineers, and product teams to ensure our ML solutions deliver value and meet business needs.

Key Responsibilities:

Design, implement, and deploy machine learning models and solutions that address business problems and enhance products and services.

Collaborate with data scientists and engineers to develop scalable data pipelines, optimize algorithms, and manage data workflows.

Analyze large, complex datasets and build predictive models and systems that improve business processes and decision-making.

Research and apply advanced machine learning techniques, such as deep learning, reinforcement learning, natural language processing, and computer vision, depending on the project needs.

Optimize the performance of ML models, ensuring they are efficient and meet performance requirements in terms of speed and accuracy.

Integrate ML models into production environments and ensure that they work seamlessly with other parts of the tech stack.

Work with cross-functional teams to define project requirements, provide technical guidance, and ensure alignment between ML solutions and business objectives.

Mentor junior team members and share knowledge to foster continuous learning and development within the team.

Stay up to date with the latest trends in machine learning, artificial intelligence, and related fields, applying new techniques and approaches to drive innovation.