
ML Engineering Manager
2 weeks ago
Job Title: ML Engineering Manager (AI/ ML Product Development)
Location: Remote (India)
Experience: 7+ years (with 2+ years in leadership roles)
Help Shape the Future of AI — Safely:
A rapidly growing AI safety team is looking for a Machine Learning Engineering Manager to lead the development of platforms and services that ensure AI innovations are deployed securely, responsibly, and with human alignment. You'll be working at the forefront of AI safety — an essential area for the future of trustworthy and ethical AI.
Why This Role Matters:
AI innovation is accelerating — and safety must evolve just as fast. This role directly contributes to building tools that allow organizations to confidently launch AI solutions without compromising on robustness, reliability, or security.
What You'll Do:
Lead a cross-functional team of ML engineers, platform engineers, and a product manager
Develop platforms for AI alignment, adversarial testing, drift detection, and interpretability
Engage with customer teams to understand real-world AI safety challenges
Translate customer needs into actionable engineering roadmaps
Drive engineering excellence through secure coding, infrastructure-as-code, and SLAs
Explore and pilot cutting-edge research in AI safety and model evaluation
What You Bring:
5+ years of software engineering experience (minimum 2 years leading teams or large-scale projects)
Proven background in ML/AI platforms, model evaluation tools, or MLOps systems
Technical expertise in Python, TensorFlow, PyTorch, Docker, Kubernetes
Familiarity with LLM architectures, prompt engineering, adversarial testing
Experience with cloud platforms (AWS, GCP, Azure)
Bonus: LangChain/LangGraph, Spark/Flink, or knowledge of AI regulatory frameworks (e.g., SOC 2, ISO 27001)
As AI becomes more powerful, the question is no longer just what it can do — but what it should do. Who ensures AI aligns with human values, remains interpretable, and resists harmful misuse? If you're excited by not just building what's possible, but shaping what's responsible — this is your calling
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