Sarvam
AI

Machine Learning Engineer

Sarvam · Bengaluru, India

Actively hiring Posted 4 months ago

We are building a scalable, AI-powered dubbing platform used across multiple languages and content formats. We are looking for a Machine Learning Engineer to help improve system reliability, performance, and production readiness through data-driven methods and automation.

Responsibilities

  • Design, build, and maintain ML systems that power the dubbing platform.
  • Develop automated validation and monitoring mechanisms to ensure consistent system behavior.
  • Optimize model inference pipelines for performance, cost, and reliability.
  • Build data and evaluation workflows to support continuous improvement.
  • Run experiments and validate changes before production rollout.
  • Collaborate with product, engineering, and operations teams to deliver high-quality features.
  • Document systems, workflows, and best practices.

Requirements (Must-have)

  • Strong foundation in machine learning and deep learning.
  • Experience deploying ML systems in production environments.
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch).
  • Good understanding of model optimization, debugging, and performance tuning.
  • Experience working with GPU-based workloads.
  • 3 to 6 years of relevant industry experience in ML/AI.

Preferred Qualifications (Bonus)

  • Experience working on speech, audio, or multimodal systems.
  • Familiarity with large-scale ML infrastructure and cloud platforms.
  • Exposure to distributed systems, containers, and orchestration tools.
  • Experience building evaluation frameworks for ML systems.

What success looks like

  • Improved stability and performance of the dubbing platform.
  • Reliable monitoring and validation systems in production.
  • Faster iteration cycles with measurable improvements.
  • Reduced operational overhead through automation.

Role details

  • Title: Machine Learning Engineer Dubbing Platform
  • Experience: 3 to 6 years
  • Location: (Onsite / Hybrid / Remote)
  • Compensation: As per industry standards

Tags & focus areas

Used for matching and alerts on DevFound
Remote Performance Tuning Automation Product Engineering Machine Learning Debugging Continuous Improvement Operations Distribution System Deep Learning
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.