Description
We are looking for a highly skilled and experienced Senior MLOps Engineer to join our team. This role involves designing, implementing, and maintaining robust and scalable machine learning pipelines. The ideal candidate will have 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 provide the tools and skills needed for your own growth. You’ll benefit from exposure to a wide range of tools and technologies, with opportunities to become certified in various Cloud and related technologies to develop your own toolkit.
Requirements
Software Engineering:
* Proficiency in programming languages used in ML, such as Python and 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 and API development.
Machine Learning (ML):
* Deep understanding of machine learning principles, algorithms, and techniques.
* Experience with 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 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 similar role, with a strong understanding of AI/ML lifecycle management.
* 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 ability to troubleshoot complex AI/ML system issues.
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 Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and MLOps frameworks/tools (e.g., Sagemaker, Azure ML, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI).
What We Offer
Culture of caring. We prioritize a culture of caring, acceptance, and belonging, fostering meaningful connections with teammates, managers, and leaders.
Learning and development. We support continuous learning through programs, training, and hands-on opportunities to grow personally and professionally.
Interesting & meaningful work. Engage in impactful projects that matter, helping clients reimagine possibilities and bring innovative solutions to market.
Balance and flexibility. We promote work-life balance with flexible roles and arrangements to help you achieve personal and professional harmony.
High-trust organization. Integrity is key; we are a reliable, ethical company where honesty and transparency are valued.
About GlobalLogic
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner helping leading companies innovate since 2000. We collaborate to transform businesses through intelligent products, platforms, and services.
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