At a Glance
- Tasks: Design and maintain scalable machine learning pipelines while collaborating with data scientists.
- Company: GlobalLogic is a leading digital engineering partner, transforming industries through innovative solutions.
- Benefits: Enjoy a culture of caring, continuous learning, and flexible work arrangements.
- Why this job: Work on impactful projects that shape the future and enhance your skills in a supportive environment.
- Qualifications: Proficiency in Python/Java, ML frameworks, and cloud platforms; strong problem-solving skills required.
- Other info: Join a high-trust organisation committed to integrity and personal growth.
The predicted salary is between 43200 - 72000 £ per year.
We are looking for a 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.
Requirements
- 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.
- 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
- Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management.
- Strong experience deploying and productionizing ML models.
- Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies.
- Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems.
Technical Insight
- Skills with MLOps concepts and principles.
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes).
- 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
- Culture of Caring: At GlobalLogic, we prioritise 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.
- 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.
- 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.
- 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.
- 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.
Senior MLOps Engineer IRC261736 employer: GlobalLogic
Contact Detail:
GlobalLogic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer IRC261736
✨Tip Number 1
Familiarise yourself with the specific MLOps tools and frameworks mentioned in the job description, such as Sagemaker pipelines, Azure ML Studio, and Kubeflow. Having hands-on experience or projects showcasing these tools can significantly boost your chances.
✨Tip Number 2
Network with current employees or professionals in the MLOps field through platforms like LinkedIn. Engaging in conversations about their experiences at GlobalLogic can provide you with valuable insights and potentially a referral.
✨Tip Number 3
Stay updated on the latest trends and advancements in machine learning and MLOps. Being able to discuss recent developments or innovations during an interview can demonstrate your passion and commitment to the field.
✨Tip Number 4
Prepare to showcase your problem-solving skills by thinking of examples where you've tackled complex issues in AI/ML systems. This will help you stand out during interviews, as the role requires strong analytical abilities.
We think you need these skills to ace Senior MLOps Engineer IRC261736
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps, machine learning principles, and relevant programming languages like Python or Java. Use keywords from the job description to demonstrate that you meet the requirements.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that align with the responsibilities of a Senior MLOps Engineer, showcasing your problem-solving skills and technical expertise.
Showcase Relevant Projects: If you have worked on any significant projects related to MLOps or machine learning, include them in your application. Describe your role, the technologies used, and the impact of the project to illustrate your hands-on experience.
Highlight Continuous Learning: Mention any certifications or courses you've completed related to cloud platforms, MLOps frameworks, or machine learning. This shows your commitment to professional development and staying updated with industry trends.
How to prepare for a job interview at GlobalLogic
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in programming languages like Python or Java, and demonstrate your understanding of MLOps concepts. Bring examples of past projects where you successfully implemented machine learning pipelines or deployed models.
✨Understand the Company Culture
Research GlobalLogic's culture of caring and their commitment to learning and development. Be ready to explain how your values align with theirs and how you can contribute to a supportive and inclusive work environment.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Brush up on your problem-solving skills and be ready to walk through your thought process when troubleshooting complex issues in AI/ML systems.
✨Familiarise Yourself with Cloud Platforms
Since the role involves working with cloud platforms like AWS, Google Cloud, or Azure, make sure you understand their services and how they relate to MLOps. Discuss any hands-on experience you have with these technologies during the interview.