Senior ML Ops Engineer

Epergne Solutions is looking for Senior ML Ops Engineer.

Experience : 6+ years

Payroll: Epergne Solutions

Locations: Chennai, Bengaluru, Pune, Hyderabad, Bhubaneshwar, Chandigarh, Gurugram

What will you need?

University Degree in Computer Science, Information Technology, or related field

6+ years of experience in the Machine Learning Operations role

Design the data pipelines and engineering infrastructure to support our clients 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 for our clients to handle machine learning training and inference

Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients 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 clients to build requirements and track progress

Strong analytic skills related to working with structured, semi structured and unstructured

datasets

Docker and Kubernetes

Experience in using popular ML Ops frameworks like Kubeflow, ML Flow, and Data Robot

Ability to build ML Ops pipelines

Strong Python programming knowledge

Kubeflow

Poetry for package management

Black, ruff, isort, flake8 for code clean up

GitHub Actions

Machine learning techniques: Decision Trees, Random Forest, Boosting Algorithm,

Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian

Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly

deduction, Natural Language Processing (incl. sentiment analysis, Topic Modelling),

Natural Language Generation

Ability to design and implement cloud solutions - Azure

Awareness of Agile / Scrum ways of working

Identify the right modelling approach(es) for given scenario and articulate why the

approach fits

Assess data availability and modelling feasibility

Review interpretation of models results

Experience in Logistic industry domain would be added advantage

You should have:

Certifications in some of the core technologies

Ability to collaborate across different teams/geographies/stakeholders/levels of seniority

Customer focus with an eye on continuous improvement;

Energetic, enthusiastic and results-oriented personality

Ability to coach other team members, you must be a team player

Strong will to overcome the complexities involved in developing and supporting data

pipelines

Ready to embark on the journey? Here s what we are looking for:

As a Senior ML Ops Engineer, having Machine Learning skill set is a huge plus.

Very good knowledge of ML Model deployment will also be an integral part of this role.

You are a technology aficionado, therefore you have a good understanding of Python, CI/CD pipeline.

You are able to work independently, prioritize and organize your tasks under time and

workload pressure.

Working in a multinational environment, you can expect cross-region

collaboration with teams around the globe, thus being advanced in spoken and written English will be certainly useful.