This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer in India.
In this role, you will work on building and optimizing advanced machine learning systems that power secure, scalable, and efficient AI-driven applications used by thousands of global customers. You will be responsible for developing and fine-tuning small language models, improving inference efficiency, and deploying models across edge, mobile, and server environments under strict performance constraints. The position requires a strong balance of research-driven ML engineering and production-focused implementation, with an emphasis on latency, scalability, and reliability. You will contribute to end-to-end MLOps pipelines, ensuring smooth transitions from data ingestion to production deployment. The environment is highly technical and collaborative, with a strong focus on applied AI innovation and real-world impact. You will also play a key role in monitoring, evaluating, and continuously improving model performance in production systems.
Accountabilities
- Fine-tune and train small language models using frameworks such as Hugging Face, TRL, and parameter-efficient methods like LoRA, QLoRA, and PEFT to improve performance and efficiency.
- Optimize machine learning models through quantization, pruning, and knowledge distillation techniques to ensure lightweight and high-performance inference.
- Design and deploy models across edge devices, mobile environments, and local servers while meeting strict latency and hardware constraints.
- Build and maintain end-to-end MLOps pipelines covering data ingestion, model training, validation, deployment, and monitoring in production environments.
- Monitor and analyze model performance metrics including accuracy, latency, and compute utilization (CPU/GPU) to ensure operational stability.
- Develop and use benchmarking frameworks and evaluation systems to continuously assess and improve model quality.
Requirements
- Strong experience in machine learning engineering, with hands-on expertise in training and fine-tuning small or large language models.
- Proficiency with Hugging Face ecosystem and adapter-based fine-tuning methods such as LoRA, QLoRA, or similar techniques.
- Solid understanding of model optimization techniques including quantization, pruning, and knowledge distillation for efficient deployment.
- Experience building production-grade MLOps pipelines, including CI/CD workflows, experiment tracking, and model versioning.
- Proven ability to deploy ML models to edge, mobile, or constrained environments with performance and latency considerations.
- Strong programming skills in Python and familiarity with ML frameworks such as PyTorch or TensorFlow.
- Experience with model monitoring, performance tuning, and system-level debugging in production environments.
- Bonus: Knowledge of ONNX export and cross-platform inference optimization.
Benefits
- Competitive salary aligned with experience and market standards.
- Comprehensive medical insurance coverage for employees and their families.
- Fully covered life insurance premiums for financial security.
- Flexible working hours with paid time off to support work-life balance.
- Gym reimbursement and wellness support programs.
- Childcare reimbursement and family-friendly benefits.
- Access to a global, innovation-driven environment focused on applied AI and scalable ML systems.
How Jobgether Works
We use an
AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
