Senior MLOps Engineer IRC261736

GlobalLogic; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An established industry player is seeking a Senior MLOps Engineer to design and maintain robust machine learning pipelines. This role involves collaborating with data scientists and software engineers to streamline the deployment and monitoring of ML models. You will gain exposure to a variety of cutting-edge tools and technologies, enhancing your skills and certifications in cloud computing. The company fosters a culture of caring, prioritizing your professional growth and work-life balance while engaging in meaningful projects that make a significant impact. If you are passionate about machine learning and want to contribute to innovative solutions, this opportunity is for you.

Benefits

Inclusive culture

Continuous learning and development

Meaningful work

Work-life balance

High-trust organization

Qualifications

• Proven experience in MLOps or similar role with strong AI/ML lifecycle management.
• Deep understanding of machine learning principles and algorithms.

Responsibilities

• Design, implement, and maintain scalable ML pipelines.
• Deploy and productionize ML models efficiently.

Skills

Python

Java

Problem-solving

Analytical skills

Machine Learning principles

Software development best practices

Data visualization

Tools

TensorFlow

PyTorch

scikit-learn

Apache Spark

Docker

Kubernetes

AWS

Google Cloud

Azure

MLFlow

Job description

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Description

We are looking for highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to streamline the deployment and monitoring of machine learning models, ensuring efficiency and reliability in ML operations.

We hire based on personality, potential, and enthusiasm to make a difference, then we give you the tools and skills you need to follow your own path. You'll benefit by gaining exposure to a wide range of tools and technologies that you can then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit.

Requirements

1. Software Engineering:
   • Proficiency in programming languages used in ML, such as Python/Java.
   • Knowledge of software development best practices and methodologies.
   • Experience with version control systems (e.g., Git).
   • Familiarity with CI/CD tools and practices.
   • Strong problem-solving and analytical skills.
   • Understanding of data structures and algorithms.
   • Ability to design and develop scalable, efficient, and maintainable software systems.
   • Experience with microservice architecture, API development.
2. Machine Learning (ML):
   • Deep understanding of machine learning principles, algorithms, and techniques.
   • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark.
   • Proficiency in data preprocessing, feature engineering, and model evaluation.
   • Knowledge of ML model deployment and serving strategies, including containerization and microservices.
   • Familiarity with ML lifecycle management, including versioning, tracking, and model monitoring.
   • Ability to optimize and fine-tune ML models for performance and accuracy.
   • Understanding of statistical analysis and experimental design.
   • Proficiency in data visualization and interpretation of ML results.

Job responsibilities

1. Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management.
2. Strong experience deploying and productionising ML models.
3. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies.
4. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems.

Technical Insight

1. Skills with MLOps concepts and principles.
2. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes).
3. Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI).

What we offer

1. Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you'll experience an inclusive culture of acceptance and belonging, where you'll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders.
2. Learning and development: We are committed to your continuous learning and development. You'll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic.
3. Interesting & meaningful work: GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you'll have the chance to work on projects that matter.
4. Balance and flexibility: We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life.
5. High-trust organization: We are a high-trust organization where integrity is key. By joining GlobalLogic, you're placing your trust in a safe, reliable, and ethical global company.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world's largest and most forward-thinking companies. Since 2000, we've been at the forefront of the digital revolution - helping create some of the most innovative and widely used digital products and experiences.