Senior Machine Learning Engineer-RK-P1
Bengaluru, Karnataka, India
Atlas Systems
Atlas Systems leads IT services with generative AI, offering tailored managed solutions, ITOps, and IT security. Based in NJ, we ensure operational excellence.About Us:
Atlas Systems Inc. is a Software Solutions company headquartered in East Brunswick, NJ. Incorporated in 2003, Atlas provides comprehensive range of solutions in the area of GRC, Technology, Procurement, Healthcare Provider and Oracle to customers across the globe. Combining our unparalleled experience of over a decade in the software industry and global reach, we have grown with extensive capabilities across industry verticals.
For more information, please visit our website https://www.atlassystems.com/
Please click on the link below to apply for this position:
https://atlas.bamboohr.com/careers/438
Senior Machine Learning Engineer (5+years)
Fulltime, Bangalore, India
Experience: 5-7 years of proven experience
Who we are looking for:
We are seeking a skilled Machine Learning Engineer with 5-7 years of experience who
combines deep analytical skills with practical implementation experience. The right
candidate will have a proven track record of developing and deploying sophisticated
ML models across various use cases. You will play a pivotal role in designing,
developing, and deploying advanced machine learning models, optimizing their
performance, and ensuring seamless integration with our software systems. You will be
expected to take ownership of projects, mentor junior team members, and contribute to
the strategic direction of our machine learning initiatives.
Key Responsibilities:
• Design and develop machine learning systems, including algorithms and deep
learning models, to solve complex business problems.
• Implement and optimize ML models using frameworks such as TensorFlow,
PyTorch, and scikit-learn.
• Conduct experiments and tests to improve model accuracy, efficiency, and
scalability.
• Build and maintain scalable data pipelines for ingestion, cleaning, and
preprocessing of large datasets.
• Collaborate with data engineers to build and maintain robust data pipelines for
model training and deployment.
• Ensure the smooth transition of models from prototype to production, including
setting up deployment pipelines and monitoring solutions.
• Participate in code reviews, design discussions, and architectural decisions to
enhance system quality.
• Mentor junior engineers and share knowledge.
• Stay updated with the latest advancements in machine learning, Agentic AI,
artificial intelligence, and related technologies.
Key Requirements:
• Education: bachelor’s or master’s degree in engineering, Mathematics,
Statistics, or a related field.
• Experience: 5-7 years of proven experience as a Machine Learning Engineer or
in a similar role.
• Technical Skills:
◦ Strong programming skills in Python, with experience in other languages
like R, C++ or Java being a plus.
◦ Proven expertise with machine learning frameworks (e.g., TensorFlow,
PyTorch, scikit-learn).
◦ Proven expertise with machine learning frameworks (e.g., TensorFlow,
PyTorch, scikit-learn) and familiarity with Agentic AI frameworks or
concepts (e.g., LangGraph, CrewAI or multi-agent systems).
◦ In-depth knowledge of data engineering principles, including ETL pipelines
and big data tools (e.g., Spark).
◦ Experience with MLOps practices, including model deployment,
monitoring, CI/CD pipelines, and containerization (e.g., Docker,
Kubernetes).
◦ Experience with distributed systems, cloud platforms (e.g., AWS, Azure,
GCP), and messaging systems (e.g., Kafka, RabbitMQ).
• Soft Skills:
◦ Exceptional problem-solving and analytical abilities.
◦ Ability to explain complex technical concepts to non-technical
stakeholders.
What We Offer:
• A role at the forefront of AI/ML innovation, influencing transformative industry
projects.
• A collaborative, growth-focused environment.
• Zero politics, merit-driven culture
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Big Data CI/CD Data pipelines Deep Learning Distributed Systems Docker Engineering ETL GCP Java Kafka Kubernetes Machine Learning Mathematics ML models MLOps Model deployment Model training Oracle Pipelines Python PyTorch R RabbitMQ Scikit-learn Spark Statistics TensorFlow
Perks/benefits: Career development
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