Vacancy description
Rearc
India, Bengaluru
Senior AI/ML Specialist in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
At Rearc, we're committed to empowering engineers to build awesome products and experiences. Founded in 2016, we pride ourselves on fostering an environment where creativity flourishes, bureaucracy is minimal, and individuals are encouraged to challenge the status quo. we're a community of problem-solvers dedicated to improving the lives of fellow software engineers and the customers we serve.
Rearc is seeking a hands-on AI Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. This position is focused on delivering real-world AI/ML solutions that address actual customer needs—not prototypes, notebooks, or one-off scripts generated by tools without deep understanding. As an AI Engineer at Rearc, you will work across the full development lifecycle, from system design to production deployment, building robust AI-powered applications that integrate into business workflows and deliver measurable impact. We value your ability to ship, evaluate, and continually improve AI systems end-to-end, rather than deep theoretical expertise or experience with proprietary model training and fine-tuning processes.
4+ years of experience building and deploying AI/ML systems in production (beyond demos or experimentation)
Preferred Experience
LLMOps/MLOps experience: building robust, monitored, self-healing AI systems
Experience with harness engineering (e.g., Databricks experience (preferred)
Experience with cloud platforms such as AWS, Azure, or GCP
Experience with FastAPI, Pydantic, PostgreSQL, MySQL, or DuckDB
Experience using the Claude SDK or OpenAI SDK
Additional programming languages beyond Python—TypeScript or Go are strong positives
Experience mentoring or upskilling fellow engineers
Design and implement AI agents, including RAG pipelines, orchestration workflows, and tool invocation
Implement observability and monitoring across the AI system lifecycle
Integrate with multiple AI providers and develop abstraction layers for multi-model architectures
Optimize AI systems for performance, cost, and scalability
Build and deploy AI-powered applications tightly coupled with real business workflows
Integrate AI systems into existing enterprise platforms and APIs
Participate in technical design discussions with a focus on implementation
We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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