Lead MLOps Engineer | Remote-Friendly
4 weeks ago
Velotio Technologies is a product engineering company working with innovative startups and enterprises. We are a certified and recognized as one of the best companies to work for in India. We have provided full-stack product development for 110+ startups across the globe building products in the cloud-native, data engineering, B2B SaaS, IoT & Machine Learning space. Our team of 325+ elite software engineers solves hard technical problems while transforming customer ideas into successful products.
Summary
This role is responsible for providing technical leadership and execution expertise to design and deliver end-to-end MLOps engineering solutions to support new product development and advanced analytics capabilities.
The Lead MLOps Engineer plays a pivotal role in bridging the gap bewteen data science and operations, ensuring smooth deployment and management of machine learning models in production environments.
You will collaborate closely with data scientists, data engineers, and data architects to build scalable, reliable, and automated machine learning pipelines.
Deploy and maintain various types of AI/ML models in production including model performance tracking and CI/CD pipelines for model retraining.
Design, develop, and maintain a Feature Store, online and offline, as needed to accelerate data science initiatives and support real-time use cases.
Design, develop, and maintain online and offline model serving.
Develop and implement standards and best practices for MLOps discipline and ensure consistency to these standards.
Work closely with data scientists, software engineers, and data engineers to ensure successful deployment and management of AI/ML models.
Develop and maintain MLOps related infrastructure.
Stay abreast of current and emerging technologies to improve efficiency, reliability, and scalability, including emerging machine learning, data management, and AI capabilities with the real-time implementation of AI/ML software.
Partner with the Lead Architect on ML architecture and solution design.
Perform design, code, and test plan reviews in support of maintaining data engineering standards
Implement a modern Model Lifecycle, in conjunction with Data Scientists and Researchers, to drive a rapid, iterative lifecycle from request to delivery of models
Develop and implement an efficient and scalable framework to take models from data scienists to fully optimized and implemented production processes
Collaborate with data scientists to prepare data for model development and production
Comply with health and safety guidelines and rules; managers should also ensure compliance across their teams.
Maintain professional and technical knowledge by attending educational workshops, reading professional publications, establishing personal networks, and participating in professional societies.
Desired Skills
5+ years of experience in data science or engineering roles, including hands-on experience designing and developing machine learning solutions
3+ years of hands-on professional MLOps engineering experience including understanding of container technology, Restful API and other various model deployment techniques and model performance
measurement in production.
Natural sense of urgency, teamwork, and collaboration reflected in daily work ethic.
Strong knowledge of modern machine learning techniques.
Expert proficiency in programming and querying languages, including Python and SQL
Proficiency in big data processing, including Apache Spark and/or Databricks.
Proficiency in technologies like MLFlow, Azure ML services, AutoML etc.
Proven track record of leading projects and cross-functional teams
Strong problem-solving and analytical thinking skills.Bachelor’s degree in computer science or related quantitative field of study or related experience
Experience working with Agile methodologies
Experience with IOT, software-defined customer experiences, private equity backed companies.
Our Culture:
We have an autonomous and empowered work culture encouraging individuals to take ownership and grow quickly.
Flat hierarchy with fast decision making and a startup-oriented “get things done” culture.
A strong, fun & positive environment with regular celebrations of our success. We pride ourselves in creating an inclusive, diverse & authentic environment.
Note: Currently, all interviews and onboarding processes at Velotio are being carried out remotely through virtual meetings.
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