2.0 - 6.0 years

0 - 0 Lacs

maharashtra

On-site

You have an exciting opportunity to join Anervea.AI as a Clinical Data Scientist in their Pune office. Anervea.AI is seeking individuals with expertise in Clinical Data, Python, GenAI, RAG Framework, LLM, HealthTech, biomedical, and Pharmaceutical domains. As a part of the team, you will be responsible for developing, training, and fine-tuning large language models and generative architectures such as LLMs, VAEs, Transformers, and GANs. You will also integrate models with applications using frameworks like LangChain, LlamaIndex, and RAG, design LLM-based agents for various use cases, and build prompt templates and semantic memory flows using vector databases like Pinecone or FAISS. In this role, you will collaborate closely with backend and data teams to ingest data from a variety of sources including PDFs, APIs, structured databases, and JSON files. It will be your responsibility to benchmark model outputs, run experiments to optimize cost, performance, and quality, and stay updated on the latest AI research to implement useful techniques in production environments. Additionally, you will be expected to write clear, modular, reusable code with proper documentation and test coverage, as well as troubleshoot any model-related deployment or inference issues that may arise. To excel in this position, you must possess strong Python programming skills and have experience with foundation models like Transformers, Hugging Face, OpenAI/Anthropic APIs, and Med-GEMMA. Familiarity with agentic frameworks such as LangChain, LlamaIndex, LangGraph, and semantic RAG, along with experience in working with vector databases like Pinecone, FAISS, or Weaviate is essential. You should also be comfortable with prompt engineering, few-shot learning, fine-tuning basics, and have the ability to process and clean unstructured data like PDFs, notes, and research papers. Understanding of NLP metrics, model evaluation techniques, and bonus experience with biomedical or clinical data will be advantageous. Moreover, familiarity with deploying models via FastAPI, Docker, or Streamlit will be considered a bonus. As a candidate, you are expected to possess certain personal attributes including curiosity, attention to detail, ownership mindset, ability to work independently, passion for building usable AI, and strong communication and collaboration skills. Bonus qualities that will set you apart include having built or deployed LLMs into production, experience with healthcare or life sciences data, and showcasing personal projects, GitHub repos, or AI experiments that reflect your passion for the field. The interview process for this opportunity will involve a technical round with the Head of Engineering at Anervea.AI. To apply for this position, you can follow the simple steps provided - Click on Apply, Register or Login on the portal, complete the Screening Form, and upload your updated resume to increase your chances of getting shortlisted for an interview with the client. At Uplers, our aim is to make hiring reliable, simple, and fast for all our talents. We are here to support you throughout your engagement and help you progress in your career. If you are ready for a new challenge, a great work environment, and an opportunity to elevate your career to the next level, apply today and take the first step towards joining our team at Anervea.AI. We are excited to welcome you on board!,

Posted 1 week ago

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Senior Data Scientist GenAI Specialist Recro

3.0 - 7.0 years

0 Lacs

karnataka

On-site

As a Data Scientist specializing in Generative AI (GenAI), you will be joining our advanced analytics team where you will be responsible for designing, developing, and deploying GenAI models using cutting-edge frameworks such as LLMs and RAG. Your role will involve building and implementing AI pipelines on cloud services like AWS, Azure, and GCP, and collaborating with cross-functional teams to integrate AI models into business applications. Additionally, you will be managing tokenization strategies, chunking, vector stores, and prompt engineering to ensure optimal GenAI performance while adhering to best practices in hallucination control and ethical AI. In this role, you will be driving research and experimentation in Knowledge Graphs, Vision APIs, and Responsible AI practices to contribute to the innovation of AI-driven business processes. Furthermore, you will collaborate with engineering teams to deploy GenAI solutions into production environments using technologies such as Docker, SQL, and versioning tools. The ideal candidate for this position must have a strong understanding of Agent Framework, RAG Framework, Chunking Strategies, LLMs, and other GenAI methodologies. Proficiency in cloud services such as AWS, Azure, and GCP is essential, along with experience in LangChain, Vector Databases, Token Management, Knowledge Graphs, Vision APIs, and Prompt Engineering. Additionally, familiarity with AI Algorithms, Deep Learning, Computer Vision, Hallucinations Control Methodology, and Responsible AI Methodology are considered good-to-have skills. Technical skills required for this role include proficiency in Python, Docker, SQL, and versioning tools like Git. Experience with at least one cloud platform (AWS, Azure, or GCP) is mandatory. Candidates applying for this position should meet the following eligibility criteria based on their experience level: - Consultant: 3+ years of relevant experience in Data Science - Assistant Manager: 4+ years of relevant experience in Data Science - Manager: 5+ years of relevant experience in Data Science Preferred candidates will have a strong background in Python programming, a track record of successful project delivery using LLMs or GenAI, and the ability to work effectively both independently and collaboratively in fast-paced environments.,

Posted 2 weeks ago

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Python Developer Innointel Global

3.0 - 5.0 years

8 - 16 Lacs

Bengaluru

Hybrid

Responsibilities include: * 3 - 5 years of experience in Python *Developing microservices using Python. * Deploying microservices as AWS Lambdas, including packaging them as Docker images when necessary. * Connecting with various data sources utilizing Python SDKs or standard REST communication. * Implementing websocket support for Python microservices. * Leveraging libraries to extract information from various document formats such as PDF, image, and Word. * Utilizing RAG frameworks like LangChain (desirable). * Developing Python programs for interacting with AWS RDS (PostgreSQL). * Employing libraries like pandas and numpy within Python microservices for data cleansing, extraction, and transformation.

Posted 2 months ago

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