Staff MLOps Engineer

1 month ago

Bangalore, Karnataka, India Ivanan Consultancy & Service Inc Full time

About the role :


For our Customer Experience AI ML COE team, we seek Hands-On MLOps Engineer who can work on designing & implementing high quality scalable data and analytics applications/platforms for large scale Machine Learning Distributed systems in agile environment. You will be part of a team deploying state-of-the-art AI ML solutions for Enphase customers.


Your ability to lead the data architecture, design, and implementation of maintainable, high-quality, and high-performing data analytics systems and AI applications is essential for success in this role. Understanding of data modelling, transformation in big data/ML environment and prior experience of building Data/MLOps pipelines using industry proven Data/ML platforms is must for this role.


What you will be doing :


- Actively seek out and solve tough data and MLOps engineering problems.


- Develop and Implement Data Arch, Data Warehouse and Hot/Warm/Cold data storage policy in cost optimized way to support AI/ML/Data use cases across the company.


- Build large scale data/MLOps pipelines with stream processing and batch processing involving high volume and variety of data.


- Build Architecture and Data/MlOps pipelines to perform data ingestion, cleansing, transformation to provide data in proper format and timely basis for predictive analytics problems.


- Design the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale


- Take offline models data scientists build and turn them into a real machine learning production system


- Develop and deploy scalable tools and services to handle machine learning training and inference


- Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems


- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.


- Support model development, with an emphasis on auditability, versioning, and data security


- Facilitate the development and deployment of proof-of-concept machine learning systems


- Communicate with stakeholders to translate business needs to technical requirements


Who you are and what you bring :


- B.E/B.Tech in Computer Science or Electrical Engineering from top tier college and >70% marks.


- 5-10 years experience designing, implementing large scale data engineering and data science distributed systems


- Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)


- Advanced, inside-out knowledge of multiple data store system in relational and NoSQL databases, messaging queues, preferably a polyglot programmer who can code in at least 2 high-level languages (Java / Ruby / Python / JS / Go / Elixir)


- Expert and hands-on experience of fault-tolerant data engineering systems (Hadoop/HDFS/Cassandra/MongoDB/Spark etc.) and multi-datacenter/cloud architectures with at-least 1 cloud platform (AWS, Microsoft Azure, GCP) preferably AWS.


- Experience working with at least one Data and Machine learning platform (AWS, Palantir, Databricks, Snowflake etc) solving big data predictive analytics problems.


- Experience developing and maintaining ML systems built with open source tools


- Experience developing with containers and Kubernetes in cloud computing environments


- Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)


- Exposure to machine learning methodology and best practices


- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)


- Experience working as part of a product team, along with engineers and product managers, to define the problem and execute the data engineering and data science solutions.


- Ability to understand business concerns and formulate them as technical problems that can be solved using data and math/stats/ML.


- Experience in dealing with large scale, noisy, and unstructured data. Experience with time series data will be advantageous


- Ability to work on a fast-paced environment & Experience with IoT based systems preferred


- Demonstrable proficiency writing clean and concise code in Java, Python or R


- Strong understanding of software testing, benchmarking, and continuous integration


- Passion for driving continual improvement initiatives on engineering best practices like coding, testing or monitoring. Excellent written and verbal communication skills

(ref:hirist.tech)

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