As a Senior ML Engineer specializing in Python for ML Platform, you will be responsible for:
Driving the development and adoption of Tigers ML platform accelerators solutions
Leading cross-functional technical teams across deep learning, machine learning, distributed systems, program management, app engineering, and product teams while working on all aspects of design, development, and delivery of machine learning-enabled end-to-end pipelines and solutions
Designing and architecting services and pipelines to support the full Machine learning Lifecycle right from Development to Deployment
Building scalable microservices architectures that can handle high volume data requests and high concurrency
Architecting solutions for High Availability, Low Latency, and High Throughput
Improving system reliability by troubleshooting and investigating any identified issues
Building and perfecting test cases to introduce highly reliable and scalable application platforms
Writing high-performance, reliable, and maintainable code
Interfacing with various interactive services and clients including web and mobile applications
Supporting the delivery of the platform solution by providing technical oversight and guidance to the respective Project Teams and ensuring High customer satisfaction
Qualifications expected from you:
6 - 10 years experience server-side/back-end full cycle product development in a production environment in Python
4+ Experience in Data Science, Statistics, Data Mining, hypothesis validation, and design of Algorithms with Strong Exposure to modern ML stack (Scikit Learn, NLP, SparkML, Pytorch Etc.)
3+ years of quality experience in Spark programming and Delta Architecture, distributed data processing. Exposure to Databricks or any managed Spark Runtime on Cloud (Dataproc / EMR)
3+ years of Experience managing production deployments in any major cloud platform - Azure/Google/AWS or on Databricks is required
3+ years of core experience as a Lead engineer in Machine learning enabled product platform in a Backend Role
Solid understanding of MLOPS related concepts, Model deployment as Batch, Real-time on a modern cloud stack
Excellent first principles understanding of Python programming and strong understanding of Data Structures and Algorithms
Proficient with SQL, RDBMS such as Postgres, MySQL, SQL Server, Oracle and/or experience with NoSQL, DBMSs such as MongoDB
Hands-on Working experience with Multiple Cloud Database technologies like Redshift, Delta, Cosmos DB, SQL Server etc. - Familiarity with some ORM (Object Relational Mapper) libraries. E.g.: SQL Alchemy
Understanding of DevOps and Deployment processes, and strong understanding of CI/CD, Technologies, and Observability
Hands-on experience in building scalable Data, ML Pipelines, Event-driven Services, and in design and deployment of ML Algorithms in Production
Comfortable with Fast Paced Development Experience Zero to One build skills
Excellent skills in terms of authoring technical specification documentation and structuring release cycles
Good understanding of Linux Fundamentals and aspects of writing Performant Code
Some experience in Python server frameworks like Flask, FastAPI
Understanding of the threading in Python, and multi-process architecture, Ray etc. - Experience in working with Event-driven architectures, Streaming data, and technologies such as Apache Kafka, Apache Nifi etc
Leveraging DFR for software, Agile, and Lean software development methodologies to drive reliability upstream into the product development life cycle
Excellent knowledge of version control (GIT), Containers etc. - Strong intuition for product development and a keen understanding of customer requirements
Proven experience managing a live product/platform and collaborating with product managers or business stakeholders to achieve business goals
Enthusiastic about creating high-performing teams and effective organizational structures
High integrity, and a great hunger to learn and develop as a software engineer
Bachelors Degree in Computer Science or related field
