Job Title: Principal AI/ML Engineer Location: Remote Company: Srotas Health Type: Full-Time ???About Srotas Health Srotas Health is an AI-driven healthcare company transforming oncology research and clinical care Our flagship platform, SrotasIQ, leverages proprietary LLMs and real-time data integration to accelerate clinical trial recruitment, automate patient pre-screening, and support clinical decision-making ??? Role Summary We are seeking a Principal AI/ML Engineer to join our core product team You will lead the architecture and development of advanced AI solutions across our platform with a special focus on patient-trial matching, real-time data ingestion, and LLM-based reasoning This is a hands-on technical leadership role with scope for influencing product direction, mentoring team members, and owning critical AI components end-to-end ???? Key Responsibilities Design, develop, and deploy robust AI/ML models for patient-trial matching, clinical summarisation, and eligibility scoring Own the architecture and scaling strategy of Srotass AI infrastructure (including LLMs, vector DBs, embeddings, and data pipelines) Lead core model experimentation (LLMs, RAG pipelines, transformer-based models, etc) and benchmarking (speed, accuracy, explainability) Collaborate with product and clinical teams to translate real-world healthcare challenges into scalable ML solutions Manage and mentor junior engineers and researchers across AI, ML Ops, and data science functions Oversee responsible AI practices including bias mitigation, model auditing, and regulatory readiness (HIPAA, GDPR) Continuously evaluate the latest research in NLP, graph learning, multimodal AI, and incorporate relevant breakthroughs into our stack ???Requirements Must-Haves: 6+ years of hands-on experience in ML/AI engineering (including production-level deployments) Deep expertise in NLP (LLMs, transformers, embeddings, RAG) Strong software engineering background (Python, TensorFlow/PyTorch, FastAPI) Experience with modern ML infra: vector databases (e-g , Milvus, Weaviate), model orchestration, and cloud ML pipelines (Azure/AWS/GCP) Proven ability to lead and deliver technical projects with ambiguity and high ownership Exposure to healthcare, clinical trials, or biomedical data (or strong interest in learning domain-specific constraints) Nice-to-Haves: Experience with FHIR, clinical ontologies (SNOMED-CT, ICD-10), or EHR data structuring Experience fine-tuning or distilling LLMs or working with OSS models (Mistral, LLaMA, GPT-NeoX) Published work or contributions to open-source AI/ML frameworks ???What We Offer Be part of the founding tech team building a cutting-edge AI platform in healthcare Competitive salary with equity options Flexible remote working policy Opportunity to shape product direction, publish applied work, and influence real-world healthcare delivery
About Srotas Health Srotas Health is an AI-first company building next-generation agentic and generative AI systems. Our core platform, SrotasIQ, leverages proprietary LLMs, multi-agent reasoning, and dynamic orchestration frameworks to deliver adaptive, high-performance AI solutions across diverse real-world use cases. Role Summary We're looking for a Senior AI Engineer who thrives on solving hard problems and scaling ambitious ideas. You'll lead the architecture and development of advanced AI systems from fine-tuning and prompt optimisation to building agentic frameworks and multi-model orchestration. This is a hands-on role for a go-getter and problem solver who's excited to work across model design, infrastructure, and product integration. You'll shape the technical foundation of our platform, guide engineering excellence, and bring cutting-edge research into production. Key Responsibilities Design, develop, and optimize LLMs, agentic systems, and multi-agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.). Lead fine-tuning, prompt tuning, and token optimization efforts to improve model accuracy, latency, and cost efficiency. Build scalable RAG pipelines, vector search layers, and reasoning agents for production use cases. Architect AI-driven workflows using transformer-based models, embedding strategies, and real-time inference pipelines. Collaborate cross-functionally to convert ambiguous challenges into deployable AI capabilities. Mentor engineers and drive best practices across ML Ops, experimentation, and performance benchmarking. Continuously evaluate and integrate advancements in LLM architectures, reinforcement learning, and agentic systems. Must-Haves 4-6 years of experience in applied AI/ML engineering, including production-level deployments. Experience with agentic frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, Dust, etc.). Experience building custom agent frameworks beyond existing libraries. Exposure to LLM fine-tuning, RLHF, LoRA, or distillation techniques. Knowledge of multi-modal agents, combining text, vision, and structured data reasoning. Open-source contributions or published work in applied AI or agent systems. Familiarity with token optimization, quantization, and inference acceleration techniques. Contributions to open-source AI/ML projects or publications in applied AI. Deep understanding of LLMs, transformers, embeddings, and RAG architectures. Proficiency in Python, TensorFlow/PyTorch, and backend frameworks such as FastAPI. Hands-on experience with vector databases (e.g., Milvus, Weaviate, Pinecone) and LLM orchestration tools. Proven ability to lead and deliver complex technical projects with ownership and agility. Compensation Opportunity to build and scale core components of a next-gen AI platform. Competitive salary with equity participation. Remote-first and flexible work culture. Freedom to experiment, innovate, and publish applied AI work. A culture that rewards initiative, creativity, and execution.
Job Title: Principal AI/ML Engineer Location: Remote Company: Srotas Health Type: Full-Time About Srotas Health Srotas Health is an AI-driven healthcare company transforming oncology research and clinical care Our flagship platform, SrotasIQ, leverages proprietary LLMs and real-time data integration to accelerate clinical trial recruitment, automate patient pre-screening, and support clinical decision-making Role Summary We are seeking a Principal AI/ML Engineer to join our core product team You will lead the architecture and development of advanced AI solutions across our platform with a special focus on patient-trial matching, real-time data ingestion, and LLM-based reasoning This is a hands-on technical leadership role with scope for influencing product direction, mentoring team members, and owning critical AI components end-to-end Key Responsibilities Design, develop, and deploy robust AI/ML models for patient-trial matching, clinical summarisation, and eligibility scoring Own the architecture and scaling strategy of Srotass AI infrastructure (including LLMs, vector DBs, embeddings, and data pipelines) Lead core model experimentation (LLMs, RAG pipelines, transformer-based models, etc) and benchmarking (speed, accuracy, explainability) Collaborate with product and clinical teams to translate real-world healthcare challenges into scalable ML solutions Manage and mentor junior engineers and researchers across AI, ML Ops, and data science functions Oversee responsible AI practices including bias mitigation, model auditing, and regulatory readiness (HIPAA, GDPR) Continuously evaluate the latest research in NLP, graph learning, multimodal AI, and incorporate relevant breakthroughs into our stack Requirements Must-Haves: 6+ years of hands-on experience in ML/AI engineering (including production-level deployments) Deep expertise in NLP (LLMs, transformers, embeddings, RAG) Strong software engineering background (Python, TensorFlow/PyTorch, FastAPI) Experience with modern ML infra: vector databases (e-g , Milvus, Weaviate), model orchestration, and cloud ML pipelines (Azure/AWS/GCP) Proven ability to lead and deliver technical projects with ambiguity and high ownership Exposure to healthcare, clinical trials, or biomedical data (or strong interest in learning domain-specific constraints) Nice-to-Haves: Experience with FHIR, clinical ontologies (SNOMED-CT, ICD-10), or EHR data structuring Experience fine-tuning or distilling LLMs or working with OSS models (Mistral, LLaMA, GPT-NeoX) Published work or contributions to open-source AI/ML frameworks What We Offer Be part of the founding tech team building a cutting-edge AI platform in healthcare Competitive salary with equity options Flexible remote working policy Opportunity to shape product direction, publish applied work, and influence real-world healthcare delivery
About Srotas Health Srotas Health is an AI-first company building next-generation agentic and generative AI systems. Our core platform, SrotasIQ, leverages proprietary LLMs, multi-agent reasoning, and dynamic orchestration frameworks to deliver adaptive, high-performance AI solutions across diverse real-world use cases. Role Summary We’re looking for a Senior AI Engineer who thrives on solving hard problems and scaling ambitious ideas. You’ll lead the architecture and development of advanced AI systems from fine-tuning and prompt optimisation to building agentic frameworks and multi-model orchestration. This is a hands-on role for a go-getter and problem solver who’s excited to work across model design, infrastructure, and product integration. You’ll shape the technical foundation of our platform, guide engineering excellence, and bring cutting-edge research into production. Key Responsibilities Design, develop, and optimize LLMs, agentic systems, and multi-agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.). Lead fine-tuning, prompt tuning, and token optimization efforts to improve model accuracy, latency, and cost efficiency. Build scalable RAG pipelines, vector search layers, and reasoning agents for production use cases. Architect AI-driven workflows using transformer-based models, embedding strategies, and real-time inference pipelines. Collaborate cross-functionally to convert ambiguous challenges into deployable AI capabilities. Mentor engineers and drive best practices across ML Ops, experimentation, and performance benchmarking. Continuously evaluate and integrate advancements in LLM architectures, reinforcement learning, and agentic systems. Must-Haves 4-6 years of experience in applied AI/ML engineering, including production-level deployments. Experience with agentic frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, Dust, etc.). Experience building custom agent frameworks beyond existing libraries. Exposure to LLM fine-tuning, RLHF, LoRA, or distillation techniques. Knowledge of multi-modal agents, combining text, vision, and structured data reasoning. Open-source contributions or published work in applied AI or agent systems. Familiarity with token optimization, quantization, and inference acceleration techniques. Contributions to open-source AI/ML projects or publications in applied AI. Deep understanding of LLMs, transformers, embeddings, and RAG architectures. Proficiency in Python, TensorFlow/PyTorch, and backend frameworks such as FastAPI. Hands-on experience with vector databases (e.g., Milvus, Weaviate, Pinecone) and LLM orchestration tools. Proven ability to lead and deliver complex technical projects with ownership and agility. Compensation Opportunity to build and scale core components of a next-gen AI platform. Competitive salary with equity participation. Remote-first and flexible work culture. Freedom to experiment, innovate, and publish applied AI work. A culture that rewards initiative, creativity, and execution.