Jobs at eka.care

Own the vision and roadmap for AI products embedded in clinical workflows. Partner with data scientists, AI engineers, and designers on model selection, prompting, retrieval, speech, tools, and agent orchestration. Define product quality evaluations, safety guardrails, and trust metrics. Translate clinical problems into product behaviors, lead enterprise and government deployments, and manage client engagements. The role requires AI product management experience, technical API and SDK fluency, and strong judgment around healthcare AI safety.

Develop and post-train large language models for safe, instruction-following clinical applications across Indian languages. Responsibilities include designing SFT and preference-optimization datasets, training reward models, building physician-guided reinforcement-learning loops, creating healthcare tool-use data, and conducting evaluations, error analysis, ablations, and red-teaming. Requires production experience with open-weight models, post-training frameworks, Python, distributed training, and strong empirical practices.

Build scalable backend systems, microservices, APIs, and data pipelines while integrating LLM-powered features and agentic workflows. Develop RAG systems using vector databases and embeddings, implement tool-calling and agent memory, and create evaluation frameworks for model quality, cost, and latency. The role also involves system optimization, testing, experimentation, and collaboration with product and frontend teams.

Execute and optimize Google and Meta performance campaigns, develop retention and lifecycle marketing initiatives, analyze funnels and cohorts, create marketing assets, and run growth experiments. Collaborate with Product, Sales, Design, and Leadership to improve acquisition, activation, engagement, retention, and business growth for healthcare AI products.

Corporate Finance Intern supporting monthly book closures, GST and TDS compliance, ESOP structuring, M&A support, fundraising execution, cap table management, and selected secretarial compliance. The role offers hands-on exposure to finance operations and strategic finance while working with senior management. Candidates should be pursuing or have completed a B.Com or MBA, understand Tally, demonstrate attention to detail, maintain confidentiality, and take ownership of assigned work.

Own EkaScribe’s clinical positioning and product roadmap, translating doctors’ workflows into adoption, retention, integration, and monetization strategies. The role partners with EMR and HMIS providers, defines clinical documentation quality, tests product hypotheses using usage data, and collaborates with data science, sales, deployment, and partner teams. Candidates must combine medical training and clinical experience with product management expertise, data skills, and understanding of health data standards.

Own 5–6 enterprise AI agent programs in parallel, primarily managing post-sales delivery and some pre-sales solutioning. Responsibilities include stakeholder management, customer communication, technical product understanding, prompt and evaluation testing, API and log analysis, success metric ownership, timelines, scope, burn, go-live, and customer feedback loops. The role connects delivery outcomes to renewals, upsells, and margin while translating customer needs into engineering-ready requirements.

Build and operate production backend systems for AI-powered clinical products, including streaming audio, ASR, LLM document generation, agent orchestration, reliability, observability, evaluation, and scalable distributed services. Own systems from design through deployment and on-call, using Python, FastAPI, AWS, Kubernetes, Redis, and PostgreSQL while collaborating with product, clinical, and mobile teams.

Own technical sales conversion from qualified lead to signed customer for ABDM Connect. Responsibilities include technical discovery, demos, solution scoping, integration walkthroughs, RFP responses, security and privacy discussions, pilot support, and collaboration with product, pre-sales, and engineering. The role serves hospital IT teams, HIS/EMR companies, and digital health organizations, translating ABDM requirements into feasible integration plans and helping customers navigate certification, consent, compliance, and data exchange requirements.

Own relationships with doctor customers across onboarding, implementation, training, adoption, retention, and satisfaction. Serve as the day-to-day contact, identify improvement opportunities, resolve concerns, coordinate with product and support teams, analyze CSAT and NPS trends, prepare client documentation, and collaborate with sales and marketing on referrals and case studies.

Own the vision and roadmap for Eka.care’s agentic AI products. Partner with data scientists and ML engineers on prompts, tools, retrieval, model selection, and multi-agent orchestration. Design rigorous LLM evaluation frameworks, safety guardrails, adversarial tests, and clinical reliability metrics. Lead enterprise and government pilots, translate client needs into product requirements, and communicate outcomes to technical, clinical, and business stakeholders.

Optimize GPU training and inference performance for medical language models. Responsibilities include profiling workloads, writing CUDA kernels, optimizing MoE communication and GEMMs, improving vLLM-class serving latency and throughput, implementing continuous batching and caching, validating AWQ/GPTQ/FP8 quantization, and enabling on-device inference for clinic hardware. The role requires hands-on GPU performance engineering, measurement-driven optimization, and correctness verification.

Build large-scale LLM training infrastructure, including corpus pipelines, distributed training workflows, evaluation tooling, experiment systems, and high-performance inference paths. The role involves training or fine-tuning billion-parameter models, operating multi-node H200 clusters, improving observability and recovery, and automating machine learning workflows. Experience with distributed computing, large-scale data engineering, and production ML systems is required.

Own end-to-end video production, including ideation, scripting, shooting, AI generation, editing, motion graphics, rendering, and delivery. Create social media, product, promotional, testimonial, explainer, and performance marketing videos across platforms. Collaborate with Design, Social Media, Performance Marketing, Content, and Product teams while experimenting with AI tools, trends, formats, and content repurposing techniques.

Design and run large-scale CPT and pre-training experiments for language models, including data-mix and curriculum ablations, proxy-scale testing, evaluation hooks, tokenization, long-context, and MoE experiments. Debug distributed training issues such as loss spikes, precision errors, dataloader stalls, and checkpoint failures. The role requires personally running pre-training or CPT at billion-parameter scale and applying rigorous empirical methods to optimize model recipes.

Build and extend evaluation harnesses, benchmark and regression tracking, data-quality tools, training monitoring, and internal research tooling for healthcare foundation models. The role includes rotating across data, evaluations, and training infrastructure with mentorship, requiring strong Python coding, defensible machine-learning fundamentals, and evidence of independently building useful projects.

Build and extend LLM evaluation harnesses, benchmark sweeps, dashboards, regression tracking, data-quality tooling, and training-run monitoring. Develop internal tools that improve research productivity while gaining experience in pretraining and post-training workflows. The role emphasizes strong Python coding, debugging, machine learning fundamentals, experimentation, and rapid learning, with opportunities to contribute to open-source medical models serving Indian-language healthcare use cases.

Support end-to-end recruitment for IT and non-IT roles by sourcing candidates, screening profiles, conducting initial conversations, coordinating interviews, managing candidate engagement, maintaining ATS records and recruitment trackers, generating reports, and assisting with offers and pre-joining activities. The role is an immediate-start, two-month, in-office internship suited to MBA HR candidates interested in talent acquisition.