BENGALURU · FULLTIME
Sr Machine Learning Engineer
Awign Enterprises
Bengaluru · onsite · Posted 41d ago
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Undisclosed6–11 yrsfulltimeBengaluru
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Section · 01
About this role
Job Summary
Role Overview
Responsibilities
Qualifications
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Job Title: Senior Machine Learning Engineer (6+ Years Experience)
Location: Mumbai, Bengaluru
Employment Type: Full-time
Role Overview
We are looking for a Senior Machine Learning Engineer to lead the development and optimization of Small Language Models (SLMs) for enterprise clients. You will drive complex model fine-tuning, knowledge distillation. As a senior technical contributor, you will mentor junior engineers, guide model selection and GPU optimization decisions, and ensure high-quality delivery across multiple concurrent client engagements.
Responsibilities
- Lead and execute complex fine-tuning and knowledge distillation pipelines for Small Language Models (1B-13B parameters) including Llama, Mistral, Phi, Qwen, and Gemma model families.
- Architect and implement production-grade RAG systems with vector database integration for domain-specific enterprise applications.
- Drive model selection decisions by evaluating performance, licensing, and deployment requirements across client use cases in FinTech, Healthcare, Insurance, and Retail verticals.
- Collaborate with MLOps engineers to optimize inference performance, including quantization (INT8/INT4), latency tuning, and GPU resource utilization on AWS infrastructure (EC2, SageMaker, EKS).
- Design and generate high-quality synthetic datasets for model training, addressing data privacy constraints and domain-specific requirements.
- Provide technical mentorship to mid-level ML engineers guiding experimentation, reviewing code, and establishing ML best practices across the pod.
- Evaluate emerging SLM architectures, fine-tuning techniques, and optimization frameworks to maintain clients competitive edge in the market.
- Support pre-sales activities by contributing to technical assessments, model benchmarking, and solution design for client proposals.
- Contribute to the development of pre-built domain-specific SLMs for priority verticals, enabling rapid deployment for future customers.
- Stay updated on SLM research, new model releases, and fine-tuning best practices through paper reading and team knowledge sessions.
Qualifications
- Engineering degree in Computer Science, Mathematics, Electrical Engineering, or related field.
- 6+ years of experience in applied ML, deep learning, or AI systems engineering.
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain).
- Proven experience with model compression, distillation, and retrieval-augmented generation workflows.
- Solid understanding of data engineering, vector databases, and modern LLM architectures.
- Excellent problem-solving, collaboration, and communication skills.
- Prior experience mentoring or leading junior engineers is a strong plus.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
CompressionDistillationdata privacyamazon web servicesenterprise applicationsAws InfrastructureAWS EC2deploymentelectrical engineeringFintechconcurrentData EngineeringHealthcareCommunication SkillsDeep LearningLangchainArtificial Intelligence
Section · Company
About Awign Enterprises
Awign Enterprises
Internet
350
employees
2016
10 years old
Bangalore / Bengaluru, Karnataka
IN
₹5.9L PA avg
Avg at Awign Enterprises
About
Awign is India’s largest work fulfillment platform for enterprises. We work with multiple large enterprises to “gigify” their core business functions and save on fixed costs.
Industries
Internet
Employee ratings
10 reviews
3.7/ 5
Culture
2.0
Career growth
2.2
Work-life
1.8
Employees rate it well for
Overall Company37Company Culture36
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