Senior Machine Learning Developer
Jobgether
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This role on the market
1,074 open learning roles across 262 companies are on ApplySarthi right now, most of them in Bengaluru (63), Hyderabad (24), Delhi NCR (14).
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What learning roles keep asking for: Machine learning (48%), Python (35%), LLMs (22%), PyTorch (22%), Deep learning (16%), AWS (13%), Generative AI (13%) — counted across their open postings here.
GCP jobs · Kubernetes jobs · LLMs jobs · Machine learning jobs
Jobgether has 3,935 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Jobgether.
Questions you are likely to be asked
- Why do you want to join Jobgether?
- What is your experience with LLMs? Tell me one thing you learned the hard way.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Senior Machine Learning Developer at Jobgether interview free →Accountabilities:: Build conversational AI systems for phone and SMS that understand customer needs, perform actions, and determine when autonomous behavior is appropriate. Develop AI tooling such as memory systems, knowledge graphs, and validated customization capabilities that enable agents to adapt to different business needs. Train, evaluate, deploy, and maintain ML models for prediction, classification, ranking, and capacity forecasting using technologies such as Ray Serve and Dagster. Create offline and online evaluations, simulations, and CI quality gates to identify regressions and continuously measure AI performance. Develop shared evaluation, observability, and LLM tooling that enables product teams to deliver AI capabilities more quickly and reliably. Contribute to ML platform capabilities including model serving, LLM infrastructure, and production monitoring. Drive engineering quality through design and code reviews, technical documentation, and mentorship. Take ownership of projects from problem definition through deployment, monitoring, iteration, and continuous improvement. Help turn lessons learned from individual product teams into reusable platform capabilities. Requirements: 6+ years of experience in software engineering or machine learning engineering, with demonstrated experience shipping ML- or LLM-powered systems to production. Strong Python skills and solid software engineering fundamentals, with an emphasis on maintainable, testable, and reliable code. Hands-on experience developing AI systems, including ML model training and deployment and/or LLM applications involving prompting, tool use, agents, retrieval, or related technologies. Strong understanding of how AI systems behave in production and the ability to identify limitations, failure modes, and quality issues. An evaluation-first mindset, with the ability to use measurement and experimentation to distinguish genuine improvements from noise or regressions. Comfort working independently in ambiguous product environments, with sound judgment around when to prioritize depth, speed, or experimentation. Strong ownership and communication skills, with the ability to take initiatives from problem framing through production delivery and ongoing improvement. Experience with ML platforms, evaluation frameworks, model serving, feature or prompt registries, or ML observability is a plus. Familiarity with technologies such as LiveKit, Ray Serve, Dagster, Vertex AI, GCP, Kubernetes, Pulumi, or AI provider APIs is beneficial. Experience taking models or AI agents from prototype to production and owning their ongoing performance is advantageous. Familiarity with real-time or streaming technologies, including voice, telephony, SIP, WebRTC, or low-latency inference, is a plus. Startup or high-growth technology experience is beneficial. Benefits: Base salary range of $200,000–$250,000 CAD . Equity package. Flexible paid time off. Fully covered group insurance. Opportunities for professional growth and career advancement. Opportunity to work on AI technology with real-world customer interactions at significant scale. Exposure to a broad range of machine learning, conversational AI, LLM, and production infrastructure challenges.
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Listed on lever · posted 2026-09-24. ApplySarthi collects openings and links to application pages; the role is advertised by Jobgether, not by us.