Jobs

Interviews
Job Alerts
Tools

Upskill and Grow with AI

Mock Interview Practice interviews in realistic simulations

Coding Practice Improve your coding skills with challenges

Certification Earn certifications to validate your skills

AI Learning Get trained with AI expert sessions

Career Path AI insights for smarter career decisions

AI Job Match Score AI-Powered Job Match Against Your Resume and Optimize Your Resume

Career Tools and Resources

Resume Builder Build Professional Resume with Ease

ATS Friendliness Check Check Resume Friendliness for Applicant Tracking Systems

Auto Apply Apply to hundreds of jobs on any platform effortlessly

Co-Pilot (Chrome Extension) Your AI Assistant for Seamless Browsing Efficiency

Interview Questions Streamline interviews with ready-to-use questions

Salaries Discover market-driven salary insights across skillsets and geographies

Companies Explore leading companies actively hiring talent
For Employers

Home
>
Jobs in chennai
>
Collar Jobskart
>
Machine Learning Engineer (Fine-tuning / Applied)

Machine Learning Engineer (Fine-tuning / Applied)

Name: Jobpe
Address: T-Hub, Plot No 1/C, Sy No 83/1, Raidurgam panmaktha, Knowledge City Rd, Hyderabad, Telangana, 500081, IN
Telephone: +91-83339-09630
Price range: Free

Collar Jobskart

3 - 8 years

0 - 3 Lacs

chennai

Posted:11 hours ago| Platform:

Apply

Skills Required

huggingface lora/qlora. fine-tuning python pytorch artificial intelligence natural language processing chatbot machine learning

Work Mode

Work from Office

Job Type

Full Time

Job Description

Machine Learning Engineer (Fine-tuning / Applied)

Location: Chennai Onsite

Experience: 3-6 years in ML/NLP

Role Overview:

You will lead the fine-tuning and evaluation of open-source LLMs (e.g., Llama, Mistral, Qwen). This

role requires hands-on skills in Python, PyTorch, Hugging Face, and distributed training frameworks.

Responsibilities:

Fine-tune and adapt open-source LLMs using LoRA/QLoRA.
Build pipelines for supervised fine-tuning and preference optimization (DPO/RLHF).
Evaluate model performance using standard and domain-specific benchmarks.
Optimize inference with quantization and serving frameworks (vLLM, TGI).
Collaborate with data engineers on preprocessing and tokenization.

Requirements:

Strong coding in Python and PyTorch.
Experience with Hugging Face, DeepSpeed, or similar frameworks.
Familiarity with distributed training and GPU optimization.
Knowledge of transformers, attention mechanisms, and NLP workflows.
Bonus: Experience in domain-specific fine-tuning (finance, legal, etc.)

More Jobs at Collar Jobskart

Hiring HR Recruiter (Non IT) - WFH

Chennai

Experience: Not specified

INR 2 - 4 Lacs

Hiring HR Recruiter (Non IT)

Chennai

Experience: Not specified

INR 2 - 4 Lacs

Hiring HR recruiters - WFH

Chennai

1 - 3 yrs

INR 2 - 3 Lacs

Hiring HR Recruiters ( Non IT ) - WFH

Chennai

Experience: Not specified

INR 2 - 4 Lacs

Hiring HR Recruiters ( Work From Home )

Chennai

1 - 3 yrs

INR 2 - 4 Lacs

Mock Interview

Practice Video Interview with JobPe AI

Start Python Interview

Start Your Job Search Today

Browse through a variety of job opportunities tailored to your skills and preferences. Filter by location, experience, salary, and more to find your perfect fit.

Job Application AI Bot

Apply to 20+ Portals in one click

Download Now

Download the Mobile App

Instantly access job listings, apply easily, and track applications.

Enhance Your Python Skills

Practice Python coding challenges to boost your skills

Start Practicing Python Now

Collar Jobskart

Recruitment

Job City

Before You Leave... Find Your Perfect Job!

Login to

Please Verify Your Phone or Email

Confirm Action

Contact Us

Machine Learning Engineer (Fine-tuning / Applied)

Experience & Salary

Skills Required

Work Mode

Job Type

Job Description

Machine Learning Engineer (Fine-tuning / Applied)

Location: Chennai Onsite

Experience: 3-6 years in ML/NLP

Role Overview:

You will lead the fine-tuning and evaluation of open-source LLMs (e.g., Llama, Mistral, Qwen). This

role requires hands-on skills in Python, PyTorch, Hugging Face, and distributed training frameworks.

Responsibilities:

Fine-tune and adapt open-source LLMs using LoRA/QLoRA.

Build pipelines for supervised fine-tuning and preference optimization (DPO/RLHF).

Evaluate model performance using standard and domain-specific benchmarks.

Optimize inference with quantization and serving frameworks (vLLM, TGI).

Collaborate with data engineers on preprocessing and tokenization.

Requirements:

Strong coding in Python and PyTorch.

Experience with Hugging Face, DeepSpeed, or similar frameworks.

Familiarity with distributed training and GPU optimization.

Knowledge of transformers, attention mechanisms, and NLP workflows.

Bonus: Experience in domain-specific fine-tuning (finance, legal, etc.)

More Jobs at Collar Jobskart