Senior Machine Learning Operations Engineer

2 weeks ago

Any LocationRemote, IN Prime Infosoft Full time

Roles And Responsibilities :

- Architect, build and integrate end-to-end life cycles of large-scale, distributed machine learning systems i.e. ML Ops using cutting-edge tools/frameworks.

- Develop tools and services for explainability of ML solutions.

- Implement distributed cloud GPU training approaches for deep learning models.

- Build software/tools that improve the rate of experimentation for the research team and extract insights from it.

- Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems.

- Lead and execute technical projects to completion. Communicate with peers to build requirements and track progress.

- Mentor fellow engineers in your areas of expertise

- Contribute to a team culture that values effective collaboration, technical excellence, and innovation.

- Collaborate with engineers across various functions to solve complex data problems at scale.

Requirements :

Must have :

- 5+ years of professional experience in implementing MLOps framework to scale up ML in production.

- Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools including training, inference, and evaluation.

- Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)

- Proficiency with ML model training frameworks (PyTorch, Pytorch Lightning, Tensorflow, etc.).

- Experience with GPU computing to do data and model training parallelism.

- Solid software engineering skills in developing systems for production.

- Strong expertise in Python.

- Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.

- Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).

- Having Geospatial / Remote sensing experience is a plus.

Competencies :

- Excellent debugging and critical thinking skills.

- Excellent analytical and problem-solving skills.

- Ability to work in a fast-paced, team-based environment.

Educational Qualifications :

- Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning, SW Engineering.

Benefits :

Why Us?

- Opportunity to work on a unique and futuristic technology setup

- Flat organizational structure and accessibility

- Best-in-class leave policy

- Additional allowances for learning, skill development, broadband, medical insurance cover, etc

(ref:hirist.tech)

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