- 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 realtime 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 realtime 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.
- 5+ years of experience in data science or engineering roles, including handson experience designing and developing machine learning solutions
- 3+ years of handson 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 crossfunctional teams
- Strong problemsolving and analytical thinking skills.
- Experience working with Agile methodologies
- Experience with IOT, softwaredefined customer experiences, private equity backed companies.
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Lead MLOps Engineer - Delhi, India - Velotio
Description
Description :
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.
Desired Skills :
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 on-boarding processes at Velotio are being carried out remotely through virtual meetings.
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