Senior Machine Learning Engineer

Summary

Join humani, an ethics-first, human-centered team building a secure and respectful digital authentication system. As a Senior Machine Learning Engineer, you will design, train, and optimize ML models using behavioral data and generative AI. This remote, part-time, hourly-paid position requires collaboration with security engineers, product managers, and UX teams. The role involves developing resilient pipelines for high-volume data, embedding fairness and transparency into models, and anticipating emerging threats. You will also mentor junior engineers and have the option to publish your work. The position is based in India, with quarterly in-person meetings in major EU cities.

Requirements

• 5+ years in machine learning, AI, or applied data science, with a portfolio of models shipped into production
• Particular experience in any of such companies: Google Research India (Bangalore), Microsoft Research India (Bangalore), Amazon AI / Alexa AI (Bangalore, Hyderabad), Adobe Research, IBM Research India, Samsung R&D Institute India (Bangalore, Noida), NVIDIA India, Intel India (AI Labs in Bangalore), Meta (Facebook) India – especially AR/VR and ML ethics divisions. Fractal Analytics – strong in applied AI, behavioral modeling, Haptik – conversational AI (acquired by Reliance), Turing.com – matches Indian engineers with global startups Observe.AI – AI for call center intelligence SigTuple – AI in healthcare diagnostics InVideo – Generative AI for video content, Yellow.ai – conversational and customer experience AI
• Proficiency in Python and frameworks like PyTorch or TensorFlow
• Deep familiarity with cloud platforms (AWS, GCP, Azure)
• Background in behavioural biometrics, time-series modelling, or generative AI
• MSc or PhD in a quantitative field—or an equivalent, proven path of practical excellence

Responsibilities

• Design, train, and optimize ML models (supervised, unsupervised, and generative) to extract meaning from behavioural patterns
• Explore and implement Gen AI techniques (e.g., transformers, GANs) for anomaly detection and pattern recognition
• Work closely with security engineers, product managers, and UX teams to integrate models into a seamless authentication product
• Develop resilient pipelines to process high-volume, high-dimensional, often noisy behavioural data
• Embed fairness, transparency, and explainability into everything you build
• Anticipate emerging threats and build robustness from day one
• Contribute to an MLOps culture rooted in clarity, reproducibility, and continuous learning
• Mentor junior engineers and, if you wish, publish your learnings and breakthroughs in the wider AI community

Preferred Qualifications

• Bonus points for experience in cybersecurity or digital authentication systems
• A mindset that sees ambiguity not as a blocker—but as potential
• Strong communication skills and a desire to lead with ethics and empathy

Benefits

• Strong hourly paid, transparently and consistently
• Work on your own time. No micromanagement. No pressure to leave your day job
• We meet face-to-face every quarter, in a major EU city, for 3 days of building, bonding, and breaking bread