Top Tech Jobs & Startup Jobs

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.