157 Llms Jobs - Page 3

Job Summary: We are looking for an innovative and technically skilled Generative AI Developer with 2 - 4 years of experience to join our team, focusing on the development and deployment of intelligent agents using Agentforce, Salesforces GenAI platform, or similar frameworks. The ideal candidate will be passionate about applying large language models (LLMs) to real-world business workflows, building conversational agents, and delivering high-impact AI-powered solutions within the Salesforce ecosystem and beyond. Key Responsibilities: • Design, develop, and deploy Generative AI agents using Agentforce, LLMs (like GPT-4), and related frameworks. • Build and integrate intelligent, context-aware workflows into CRM, support, and operational systems. • Collaborate with cross-functional teams (Product, Engineering, Data, and Business) to understand business challenges and deliver scalable AI solutions. • Fine-tune and prompt LLMs for specific use cases such as market outreach, sales assistance, document summarization, and automation tasks. • Maintain and optimize agent performance through evaluation, prompt engineering, and feedback loops. • Stay up-to-date with the latest in generative AI, Salesforce AI tools (Einstein Copilot, Agentforce), and open-source frameworks. • Create technical documentation and provide support for production deployments and ongoing enhancements. Qualifications Required : • 2 - 4 years of experience in AI/ML or Software Development, with at least 1 year working directly with LLMs or GenAI applications. • Hands-on experience with Agentforce, OpenAI, LangChain, or other GenAI frameworks. • Proficiency in Python, JavaScript, or relevant programming languages for AI agent development. • Experience integrating GenAI capabilities into Salesforce, web apps, or enterprise systems. • Strong understanding of prompt engineering, vector databases, and agent orchestration. Preferred : • Experience with Salesforce Einstein Copilot, Salesforce Data Cloud, or MuleSoft integration. • Familiarity with LLMOps, model evaluation, or responsible AI best practices. • Knowledge of REST APIs, OAuth, and cloud platforms (AWS, GCP, Azure). Preferred candidate profile

Key Responsibilities: Collaborate closely with Machine Learning and Engineering teams on advanced data extraction technologies (e.g., no-OCR, VLM-based extraction) Translate business needs into epics and user stories for development teams Align product goals with company strategy in coordination with Product Management Maintain a well-prioritized product backlog based on business value Work with stakeholders and data analysts to ensure data-driven product decisions Track product progress, performance, and deliverables across sprints Communicate effectively with globally distributed teams and stakeholders Stay updated with agile practices, ML/AI trends, and industry standards Required Experience & Qualifications: 3+ years as a Product Owner in an agile environment Familiarity with AI/ML patterns (e.g., VLM, LLMs) and experience working with ML-driven teams Technical aptitude with a fast-learning mindset Strong data orientation and analytical thinking Agile and/or SAFe framework knowledge Excellent attention to detail and communication skills Comfortable working in international, cross-functional environments Proficient in spoken and written English Nice to Have: Exposure to Regulatory Compliance Product Marketing experience Strong cross-cultural communication Advanced data analysis capabilities Knowledge of Biometric Security Standards

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Senior Principal Consultant - AI Senior Engineer! In this role you&rsquoll be leveraging Azure&rsquos advanced AI capabilities or AWS Advance Ai capability, including Azure Machine Learning , Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence,AWS Sage Maker, AWS Bedrocks to deliver scalable and efficient solutions. You will also ensure seamless integration into enterprise workflows and operationalize models with robust monitoring and optimization. Responsibilities . AI Orchestration - Design and manage AI Orchestration flow using tools such as: Prompt Flow, Or LangChain Continuously evaluate and refine models to ensure optimal accuracy, latency, and robustness in production. . Document AI and Data Extraction, Build AI-driven workflows for extracting structured and unstructured data fromLearning, receipts, reports, and other documents using Azure AI Document Intelligence, and Azure Cognitive Services. . RAG Systems - Design and implement retrieval-augmented generation (RAG) systems using vector embeddings and LLMs for intelligent and efficient document retrieval Optimize RAG workflows for large datasets and low-latency operations. . Monitoring and Optimization - Implement advanced monitoring systems using Azure Monitor, Application Insights, and Log Analytics to track model performance and system health Continuously evaluate and refine models and workflows to meet enterprise-grade SLAs for performance and reliability. . Collaboration and Documentation - Collaborate with data engineers, software developers, and DevOps teams to deliver robust and scalable AI-driven solutions Document best practices, workflows, and troubleshooting guides for knowledge sharing and scalability. Qualifications we seek in you Minimum Qualifications . Proven experience with Machine Learning, Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence, AWS Bedrock, SageMaker Proficiency in building and optimizing RAG systems for document retrieval and comparison. . Strong understanding of AI/ML concepts, including natural language processing (NLP), embeddings, model fine-tuning, and evaluation Experience in applying machine learning algorithms and techniques to solve complex problems in real-world applications Familiarity with state-of-the-art LLM architectures and their practical implementation in production environments Expertise in designing and managing Prompt Flow pipelines for task-specific customization of LLM outputs. . Hands-on experience in training LLMs and evaluating their performance using appropriate metrics for accuracy, latency, and robustness Proven ability to iteratively refine models to meet specific business needs and optimize them for production environments. . Knowledge of ethical AI practices and responsible AI frameworks. . Experience with CI/CD pipelines using Azure DevOps or equivalent tools Familiarity with containerized environments managed through Docker and Kubernetes. . Knowledge of Azure Key Vault, Managed Identities, and Azure Active Directory (AAD) for secure authentication. . Experience with PyTorch or TensorFlow. . Proven track record of developing and deploying Azure-based AI solutions for large-scale, enterprise-grade environments. . Strong analytical and problem-solving skills, with a results-driven approach to building scalable and secure systems. Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

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( Immediate Joiners ) Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets.

Role Overview: As an Engineering Manager in the AI team, you will lead and mentor a team of 10+ software engineers working on a wide range of AI/ML/GenAI-driven initiatives. You will be responsible for the end-to-end delivery of AI solutions, guiding your team through the full software and machine learning lifecycle, from ideation and design to deployment and continuous improvement. In this hands-on leadership role, you will collaborate closely with engineering leaders, data scientists, product managers, and other stakeholders to deliver high-quality AI applications that power our products and services. Responsibilities: Leadership and Mentorship: Lead, mentor, and develop a team of 10+ AI/ML software engineers, fostering a culture of growth, collaboration, and technical excellence. Ensure high performance by providing regular feedback, coaching, and career development opportunities. AI/GenAI Architecture and Delivery: Oversee the design and delivery of AI and generative AI systems, ensuring that all solutions are scalable, robust, and high-quality. Guide your team to implement innovative AI models, tools, and infrastructure that drive business outcomes. Cross-Functional Collaboration: Partner with other engineering leaders, data scientists, product managers, and directors to align on strategic goals and deliverables. Collaborate closely with cross-functional teams to break down complex engineering tasks and drive the execution of the AI roadmap. Agile Leadership: Lead your team in an agile environment, participating in sprint planning, daily stand-ups, code reviews, and retrospectives. Help the team manage competing priorities while maintaining focus on delivering high-quality AI solutions. Technical Excellence: Promote best practices in software development, code quality, testing, and deployment. Drive the adoption of modern engineering practices like CI/CD, automated testing, and cloud-based AI/ML solutions to ensure the delivery of secure, scalable AI applications. Innovation: Stay up to date with the latest advancements in Generative AI and machine learning. Foster a culture of continuous learning, encouraging engineers to grow their technical skills and experiment with emerging technologies to contribute to the company's thought leadership in AI. Stakeholder Communication: Act as a liaison between the AI team and other stakeholders, effectively communicating progress, risks, and technical insights to non-technical leadership and product teams. Qualifications: Experience: 7-10 years of experience in software engineering, with at least 2-4 years in a leadership or management role, overseeing AI or machine learning teams. Proven track record of leading and delivering AI/ML and Generative AI initiatives at scale in fast-paced, dynamic environments. Technical Skills: Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. Strong experience with AI, machine learning, and deep learning technologies as well as solid understanding of the software development lifecycle, object-oriented programming, concurrency, design patterns, RESTful services, and microservice architecture. AI Tools and Cloud Technologies: Experience with cloud platforms (AWS, Google Cloud, Azure), with a focus on AI/ML deployment (e.g., VertexAI, GKE, BigQuery, Kubeflow, TensorFlow Serving). Familiarity with MLOps practices and tools for model deployment and monitoring (e.g., Terraform, GitHub Actions, Concourse). Leadership and Collaboration: Strong people management and leadership skills, with experience leading cross-functional teams. Proven ability to mentor engineers, manage competing priorities, and align team efforts with business objectives. Agile Experience: Strong understanding of agile methodologies, with experience leading teams in an agile environment. Knowledge of best practices for managing sprints, tasks, and project timelines. Communication: Excellent verbal and written communication skills. Ability to communicate complex technical concepts to non-technical stakeholders and build strong working relationships across the organization. Preferred Qualifications: Experience working with large language models (LLMs) or fine-tuning open-source models like GPT. Familiarity with modern AI development tools, such as Jupyter notebooks, Kubernetes, Docker, and CI/CD pipelines. Experience in high-compliance or enterprise-grade environments with a focus on AI ethics, privacy, and security. Education: Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field. Ph.D. is a plus.

Job Description: Python Training, Internship and Job Assistance Position: Python Intern Location: Pune, Maharashtra, India Duration: 6 months Mode: Offline Stipend: Unpaid Training Program: Free Training with Job Assistance upon Successful Completion Pre-Placement Offer (PPO) Opportunity: 2.5 LPA CTC (Based on performance) Note: CANDIDATES SHOULD BE READY TO LEARN NEW TECHNOLOGIES About the Role: We are seeking a motivated and detail-oriented Python Intern to join our team. The ideal candidate will have a foundational understanding of API development using frameworks like Flask and FastAPI, a strong grasp of Python libraries such as Pandas and NumPy, and a knack for problem-solving. Knowledge of data analytics tools and Large Language Models (LLMs) will be considered a plus. Key Responsibilities: Develop and maintain RESTful APIs using Flask and FastAPI. Work with data manipulation and analysis libraries like Pandas and NumPy. Assist in building scalable and efficient back-end solutions. Solve real-world problems with logical and analytical thinking. Support data analytics efforts using tools like Power BI (preferred). Collaborate with cross-functional teams to understand requirements and deliver solutions. Explore and implement applications of LLMs and other advanced technologies (as needed). Requirements: Proficiency in Python programming. Hands-on experience or knowledge of Flask and FastAPI frameworks. Familiarity with data analysis libraries such as Pandas and NumPy. Strong problem-solving and logical thinking skills. Good understanding of RESTful API design principles. Knowledge of data analytics tools like Power BI is a plus. Awareness of Large Language Models (LLMs) and their potential applications is a bonus. Eagerness to learn and work in a collaborative environment. What We Offer: Hands-on experience in API development and data analytics projects. Mentorship from experienced professionals. Opportunity to explore cutting-edge technologies like LLMs. A learning-focused environment to develop both technical and analytical skills. Potential for full-time opportunities based on performance.

Role & responsibilities We are seeking an enthusiastic and highly skilled Senior AI ML Developer to join our team and work on exciting AI initiatives. The ideal candidate should have worked in CRM Domain like Zoho CRM/ Fresh works and have expert knowledge in AI/ML models, LLMS, Vector database and RAG techniques to automate workflows, create conversational analytics assistants and create similarity models by clustering/ embeddings. 1. Develop CRM Agentic AI Design and implement AI agents using frameworks like Lang Chain, AutoGPT, or ReAct. Automate CRM processes by enabling agents to handle emails, generate follow-ups, update pipelines, and classify tickets. Integrate models for sentiment analysis, intent recognition, entity extraction, and summarization. Connect agents to external APIs, calendars, and CRM tools (e.g., Salesforce, HubSpot). Manage agent memory and context via vector databases like FAISS or Pinecone. 2. Conversational KPI Dashboard Assistant Build a chatbot interface that allows users to query CRM KPIs via natural language. Use Python, LangChain, and OpenAI APIs to parse queries and trigger backend data retrieval tools. Render results in both dashboard format (e.g., Recharts/Chart.js) and tabular views. Support queries like "Whats the total expected revenue this quarter?" or "Show me the lead-to-win ratio by region." 3. Similarity and Recommendation Engines Extract features from existing AI/ML libraries. Build and manage an embedding database for semantic similarity search. Implement clustering algorithms (e.g., K-Means) to group songs based on genre. Develop a scoring system to compare new tracks to a database of existing songs. Required Experience and Qualifications: 4+ years of experience in AI/ML Model development. Should have expert knowledge in CRM Domain including workflows, Forms, Dashboards/reports and data import/export as done. Proficient in Python, with strong experience in TensorFlow, PyTorch, and Scikit-learn . Working knowledge of LangChain, AutoGPT and LLM integration. Expertise in developing Agents for CRM, Dashboards in Leading organisation. Expertise in implementing Agentic AI solutions using LLM models, RAG and Vector database. Proven experience in vector similarity, embedding models and clustering techniques. Passionate about AI innovation and solving real-world challenges with automation and intelligence Proven experience in designing platform architecture and managing API integrations. Strong background in microservices architecture and REST API design. Demonstrated experience with scalability and performance optimization for cloud-based platforms. Experience with Agile methodologies and leading cross-functional teams in a fast-paced environment. Excellent communication and presentation skills for delivering product demos and gathering customer feedback. Proven ability to manage a product roadmap and deliver on tight deadlines . Experience with data security , compliance, and industry best practices. A bachelors degree in computer science, engineering, or a related field.

Responsibilities: * Design, develop, test & maintain software solutions using Python, React, AWS, Kubernetes, LLMs, Langchain & Crewai. * Collaborate with cross-functional teams on project delivery & technical strategy.

Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What we're looking for Bachelor's/Master’s degree in computer science, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). Experience with LLM-specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Role Description Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation.

Gainwell Technologies LLC Summary Gainwell Technologies is seeking a highly skilled AI Engineer to design, develop, and deploy advanced AI and Generative AI (Gen AI) solutions, across our healthcare technology platforms. This role involves building and optimizing AI / GEN AI technologies, integrating them into existing systems, and ensuring their effectiveness in improving healthcare outcomes and operational efficiency while maintaining compliance with industry standards. Your role in our mission AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js What we're looking for Master’s or Ph.D in Computer Science, AI, Data Science, or a related field. 4+ years of experience in AI/ML engineering, with a focus on developing and deploying AI solutions. Hands-on expertise in machine learning, deep learning, Gen AI ( multi modal LLMs), NLP, and computer vision. Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. Experience developing, deploying and finetuning LLMs (GPT, Gemini, Claude or similar) for real world applications including prompt engineering, model optimization and inference efficiency. Experience with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments. Proficiency in working with big data technologies (Spark, Hadoop, SQL, NoSQL databases). Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Performance Optimization – Continuously monitor, refine, and optimize AI / GEN AI models for accuracy, efficiency, and speed, leveraging ML Ops and LLM Ops best practices. AI Research & Innovation – Stay updated with the latest AI/ML/ GEN AI advancements, exploring new technologies and methodologies to enhance solution effectiveness. Compliance & Security – Ensure AI implementations adhere to healthcare industry regulations, ethical AI principles, and data privacy standards. Automation & Workflow Enhancement – Identify opportunities to automate workflows and optimize business processes using AI-driven solutions. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js

Experience 9-13 years Location: Gurgaon/Noida Education: BE/B. Tech./Master of Computer Application Work Experience: Overall 9+ years of quality engineering experience with DWH/ETL for enterprise grade applications Hands on experience with functional, non-functional and automation of products Hands on experience with leverage LLMs/GenAI for improving efficiency & effectiveness of overall delivery process Role & Responsibilities: Leading end-to-end QE for product suite Authoring QE test strategy for a release and executing it for a release Driving quality releases by closely working with development, PMs, DevOps, support and business teams Achieving automation coverage for product suite with good line coverage Manage risks and resolves issues that affect release scope, schedule and quality Work with product teams to understand impacts of branches and code merges, etc. Lead and co-ordinate the release activities including the execution of overall Ability to lead team of SDETs and help them in addressing their issues Mentoring and coaching members in the team Technical Skills: Experience in ETL / BI Testing, using any ETL and Reporting Tool with Oracle / SQL Server / as Database Exposure to Data Warehousing and Dimensional Modelling Concepts Hands-on with coding preferably Python Extensive experience in writing and troubleshooting SQL Queries Ability to achieve good functional coverage of product suite Hands on experience with automation tools (Selenium, TestNg, etc.) Experience with CI/CD tools e.g., Jenkins Experience with tools like JIRA, Confluence, SharePoint, TestRails, Zephyr etc. Experience with performance, volume and stress testing Solid understanding of cloud services platforms e.g., AWS, GCP, Azure etc. Well versed with DBs and SQLs Hand-on experience with GenAI/LLMs/RAGs/Agents Soft Skills: Excellent communication skills. Ability to convey hard/sensitive messages without any apprehensions as well as avoid creating frictions. Ability to navigate through organization independently. About AXTRIA (www.axtria.com) Axtria is a global provider of cloud software and data analytics to the Life Sciences industry. We help Life Sciences companies transform the product commercialization journey to drive sales growth and improve healthcare outcomes for patients. We are acutely aware that our work impacts millions of patients and lead passionately to improve their lives.

About Us We are a dynamic software testing company with a cutting-edge AI end-to-end testing platform. As a fast-growing startup, we are driven by innovation and a commitment to building intelligent, scalable solutions. We're expanding our content team and looking for a passionate junior content writer who thrives in a fast-paced, collaborative environment. Role Overview As a Junior Content Writer, you'll play a key role in supporting our content and SEO teams. Youll be responsible for producing high-quality written content that communicates our brand effectively and helps us reach our target audience through insightful, original writing. Key Responsibilities Write and edit blog posts, search-optimized articles, website content, and product-related copy Proofread and ensure grammatical accuracy and consistency across all written materials Conduct thorough research to support content accuracy and credibility Assist the content and SEO teams in producing compelling, keyword-rich content Adapt writing style to suit different platforms and target audiences Meet tight deadlines while maintaining quality and attention to detail Requirements Bachelors or Masters degree in Journalism, Mass Communication, Marketing, or related fields 12 years of professional content writing experience, especially in IT and tech domains Comfortable working with technical subject matter; our content often involves topics like software testing, AI/LLMs, test automation, and so on (You dont need to code, but you must be curious and willing to understand) Excellent command of written English with flawless grammar and style Strong research skills and a genuine ability to produce original content (not AI-generated or stitched) Knowledge of SEO principles and ability to apply them to content writing Responsible, accountable, and committed to producing high-quality work on time Team player with a respectful, collaborative attitude Strong work ethic and a willingness to learn and grow How to Apply: Interested candidates are encouraged to submit their resume and a brief cover letter outlining their interest in the position to [HIDDEN TEXT]

Job Description: Python Gen AI Developer Seeking an experienced Python Developer with expertise in Generative AI to join our AI & ML Engineering team. The ideal candidate will work on building intelligent applications leveraging large language models (LLMs) and deep learning to enhance customer experience and streamline business processes. Key Responsibilities: Design, develop, and deploy GenAI solutions using Python and modern AI frameworks. Work with LLMs (e.g., GPT, LLaMA, Claude) and fine-tune them for enterprise use cases. Develop prompt engineering strategies and support prompt optimization. Integrate AI models with backend services and data pipelines. Implement scalable and secure APIs and services for GenAI use cases. Collaborate with data scientists, ML engineers, and product teams. Ensure compliance with enterprise security, data governance, and regulatory standards. Required Skills: 5+ years of experience with Python in enterprise application development. Strong knowledge of GenAI tools (OpenAI, HuggingFace, LangChain, etc.). Experience with LLMs, prompt tuning, RAG (Retrieval Augmented Generation). Experience with Flask/FastAPI or similar frameworks. Familiarity with vector databases (e.g., FAISS, Pinecone). Understanding of NLP and transformer models. Good knowledge of Git, Docker, CI/CD. Nice to Have: Knowledge of Azure OpenAI or AWS Bedrock. Experience working in the finance or banking domain. Exposure to Kubernetes and model deployment pipelines

Role: Python with Gen AI Developer Exp: 7+yrs Budget: Max 28 LPA Location: Bangalore (Hybrid) Must Have: Python libraries and frameworks,Generative AI, Prompt Engineering. Immediate to 30 Days. Ragul 8428065584

We are seeking a Data Scientist to help drive AI-driven insights and solutions, leveraging both traditional machine learning and Generative AI (GenAI). This role focuses on data exploration, predictive modeling, and extracting actionable insights from structured and unstructured data. You will work closely with business teams to translate challenges into AI-powered solutions, using advanced analytics, machine learning, and large language models (LLMs). Key Responsibilities: Conduct exploratory data analysis (EDA) to uncover patterns, trends, and insights. Develop and implement predictive and prescriptive models to support data-driven decision-making. Work with large datasets and apply techniques in statistics, probability, and optimization. Fine-tune large language models (LLMs) for text analytics, summarization, and conversational AI. Leverage Generative AI for knowledge retrieval, document automation, and personalization. Work on A/B testing, experimentation, and causal inference to evaluate AI model effectiveness. Collaborate with business teams to identify AI opportunities and present insights through visualizations. Use vector databases, retrieval-augmented generation (RAG), and prompt engineering for GenAI applications. Assist AI/ML Engineers in transitioning models from research to production while ensuring interpretability and explainability. Stay updated on the latest ML algorithms, generative AI advancements, and statistical techniques. Required Skills & Qualifications: Bachelor's/Master's/PhD in Data Science, Statistics, Mathematics, or a related field. Strong proficiency in Python, SQL for data analysis and modeling. Hands-on experience with statistical modeling, hypothesis testing, and feature engineering. Experience in ML frameworks (Scikit-learn, TensorFlow, PyTorch) and working with LLMs (e.g., GPT, BERT etc). Knowledge of time-series forecasting, clustering, and anomaly detection techniques. Familiarity with NLP, embeddings, and GenAI-driven analytics. Strong experience with data visualization tools. Ability to translate data insights into business impact and storytelling. Exposure to A/B testing, experiment design, and optimization algorithms. About Avaali Headquartered in Bangalore, started in 2013, Avaali Solutions is a leading provider of digital solutions to help reduce operational costs for upper mid to large enterprises. The company has executed over 120+ engagements for large marquee brands across Asia, MEA, and parts of Europe. The company has its product line under Velocious as well as its services and consulting offerings in partnership with various technology vendors. The company has done some of the largest and most complex shared service automation projects and consolidated, standardized, and automated these processes. As a result of their engagements, they have brought about a 35-50% reduction in process cycle time and a 10-15% reduction in cost. Improved visibility, governance, and transparency are other themes that Avaali focuses on via these initiatives. The company has deep skills in technologies such as ML-based ICR/OCR, enterprise content management, workflow automation solutions, chatbot, RPA, and digital signature. The company has a dominant presence in procure-to-pay automation with over 100+ implementations in this space. Some of the prominent clients of Avaali Solutions are Tata Sky, Titan, Sun TV, Bidco Africa, Nayara Energy, and many more.

Hands-on AI & ML Development: Build, train, and deploy ML models from classical techniques (Classification, Regression, Forecasting) to advanced deep learning, LLMs, and Generative AI. Perform feature engineering, statistical analysis, and model tuning to enhance predictive capabilities. Work with big data tools (Hadoop, PySpark, Hive) to process large datasets efficiently. Develop AI-driven solutions tailored for industries like Retail, CPG, BFSI, Healthcare, and eCommerce. Optimize and automate machine learning pipelines for scalable deployment. End-to-End AI/ML Deployment: Own the full ML lifecycle , from development to deployment and monitoring. Collaborate with Data Engineering teams to build production-ready ML pipelines. Work with cloud platforms such as Azure, AWS, GCP, or Databricks for model deployment and monitoring. Design and implement A/B testing strategies to measure model impact. Project Execution & Delivery: Drive multiple AI/ML initiatives from concept to execution , ensuring quality and timely delivery. Partner with cross-functional teams (Product, Data Engineering, Business) to translate business problems into scalable AI solutions . Own project roadmaps, track milestones, and ensure stakeholder alignment. Communicate AI/ML concepts effectively to both technical and non-technical stakeholders . Leadership & Team Growth: Lead by doing mentor and guide a high-performance team of data scientists. Set technical direction, review code, and establish best practices in AI/ML development. Foster a culture of continuous learning, innovation, and hands-on problem-solving . Provide career development guidance and help team members achieve technical excellence. What You Bring to the Table: 8+ years of hands-on experience in Data Science & AI , with strong expertise in ML, Python, and SQL . Exposure to Generative AI Should have worked on at least a few POCs or pilot projects leveraging Gen AI capabilities Deep understanding of ML algorithms , including NLP, LLMs, forecasting, and optimization techniques. Proven track record of building and deploying machine learning models in production environments. Expertise in at least one cloud platform: AWS, Azure, GCP, or Databricks . Strong grasp of statistics, probability, and causal inference . Ability to break down complex AI concepts for business stakeholders. Experience with big data tools (Hadoop, Hive, PySpark) and ML workflow automation . Bonus: Experience with Google Analytics, Adobe Analytics, or digital marketing analytics .

Responsibilities : Build and deploy GenAI applications using LLMs, prompt engineering, and RAG frameworks. Hands-on with prompt engineering, RAG, LLM fine-tuning, and deployment workflows. Implement AI-driven solutions for analyzing, understanding, and migrating legacy codebases. Utilize AI tools to analyze complex legacy systems, identify business logic, dependencies, and potential risks associated with migration. Integrate APIs like OpenAI, Claude, Azure OpenAI, etc., into products or tools. Develop reusable components for prompt handling, embeddings, vector search, etc. Collaborate with designers, BAs, and QA teams to iterate on MVPs and features. Optimize performance, prompt quality, and latency in GenAI pipelines. Requirements : Proficiency in Python, LangChain, LangGraph and GenAI APIs. Hands-on experience with vector databases (Pinecone, FAISS, ChromaDB). Understanding of Agentic AI, LLMs, transformers, and orchestration frameworks. Exposure to cloud services (AWS/GCP/Azure) and CI/CD practices. Stay current with AI trends and tools. Role & responsibilities

About Position: We are conducting an in-person hiring drive for the position of GenAI Developer / Sr. GenAI Developer in Hyderabad. We are looking for an experienced and talented GenAI Developer/Sr. Gen AI Developer to join our growing data competency team. The ideal candidate will have a strong background in working with GEN AI , ML ,LangChain, LangGraph, Agentic AI Microservices (Fast API), Prompt engineering. You will work closely with our data analysts, engineers, and business teams to ensure optimal performance, scalability, and availability of our data pipelines and analytics. Role: GenAI /Sr.GenAI/ RAG / LLM Engineer Interview Location: Gate 11, Argus Block-Sattva Knowledge City, 6th Floor Beside T-hub, Silpa Gram Craft Village, Madhapur Rai Durg, Hyderabad, 500081 Experience: 4 Years-8 Years Job Type: Full Time Employment Note: After joining candidate can work from AII PSL Locations What You'll Do: Develop and fine-tune LLMs for real-world use cases Build and optimize RAG pipelines using Langchain or similar tools Integrate GenAI capabilities into enterprise applications Hands on Python coding exp Work with vector databases and embedding techniques Collaborate with cross-functional teams on AI-driven features Expertise You'll Bring: 4+ years of experience working with data science. Strong proficiency in prompt Engineering and Lang chain and Fast API Experience in Microservices (Fast API), RAG and OpenAI Experience with ML/Ops technologies Understanding of machine learning fundamentals, optimization techniques, generative AI, NLP, LLMs, and Retrieval-Augmented Generation (RAG). Strong analytical, problem-solving, and troubleshooting skills. Ability to work independently and in a collaborative team environment. Python, PyTorch/TensorFlow LLMs (OpenAI, LLaMA, HuggingFace) RAGframeworks (Langchain, LlamaIndex) FAISS, Weaviate, Pinecone Cloud (AWS/GCP/Azure Databricks) Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents Inclusive Environment: Persistent Ltd. is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds. We offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities. If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry's best Let's unleash your full potential at Persistent "Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind."

Experience: 2 + years Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Office (Pune) Placement Type: Full Time Permanent position Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost As an ML / Data Science Engineer at Anervea, youll work on designing, training, deploying, and maintaining machine learning models across multiple products. Youll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. Youll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomesnot just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions

We seek a hands-on Delivery Lead with 1012 years of experience to own end-to-end execution of AI/ML projects, mentor technical teams, and collaborate with sales to scale our consulting solutions. Key Responsibilities 1. Project Delivery Own client-facing AI/ML projects from scoping to deployment, ensuring quality, timelines, and business impact. Guide teams on architecture, model design, and deployment (cloud/on-prem). 2. Team Leadership Lead and mentor data scientists/engineers, fostering skill growth and collaboration. Drive best practices in AI/ML (LLMs, MLOps, Agile). 3. Sales Collaboration Partner with sales to scope proposals, estimate efforts, and present technical solutions to clients. Must-Have Skills 10-12 years in AI/ML, with 5+ years leading teams in consulting/client delivery. Expertise in: o AI/ML frameworks (TensorFlow, PyTorch, LLMs). o Cloud platforms (AWS/Azure/GCP) and CI/CD pipelines. o Python/R, data engineering (Spark, Kafka). Strong communication and client/stakeholder management. Good to Have Familiarity with MLOps (Docker, Kubernetes). Agile/Scrum certification. Qualifications Bachelors/Masters in CS, Data Science, or related field. Certifications (e.g., AWS ML, Azure AI Engineer) are a plus.

Job Description: Data Science Trainer We're seeking a committed Technical Data Science Trainer to join us in delivering the next generation of AI technical training. This is not just a job - it's an opportunity to play a key role in empowering the next generation of AI/ML professionals, influencing their careers and contributing to the growing AI ecosystem. The role also helps get recognized as a leader in the AI training space while expanding your personal and professional brand This role is ideal for someone passionate about both teaching and technology, capable of helping learners become skilled professionals in AI and related fields. Skills: AI, Machine Learning, Python, Numpy, Pandas, R Programming, Statistics, Computer Vision, Natural Language Processing, LLMs, Tableau, Power BI Essential Qualifications: B.Tech., M.Tech., MCA or equivalent experience 2 - 6 years' of experience Expertise Required: Technical Expertise: Proficient in AI, ML, Deep Learning, LLMs, Computer Vision, and Python. Tools and Frameworks: Hands-on experience with TensorFlow, PyTorch, Scikit-learn, OpenCV, Hugging Face, NumPy, Pandas, Matplotlib, Seaborn, and R Programming. Communication: Strong ability to explain technical concepts in simple terms and provide clear instructions. Problem-Solving: Ability to debug code, identify errors, and explain solutions effectively. Key Responsibilities: Training Delivery: Design and deliver training programs and workshops for individuals and teams on AI, ML, Deep Learning, LLMs, Computer Vision, and Python programming. Adapt training methods to suit varying levels of expertise, from beginner to advanced learners. Curriculum Development: Develop structured, up-to-date course materials, including slide decks, coding exercises, case studies, and hands-on projects. Incorporate real-world applications and industry best practices into the curriculum for a practical learning experience. Regularly update course content to align with advancements in technology and industry trends. Hands-On Learning: Guide learners through practical exercises, coding labs, and project-based learning to ensure hands-on experience with tools, frameworks, and algorithms. Provide training on key frameworks and tools such as TensorFlow, PyTorch, OpenCV, Hugging Face, Scikit-learn, and Pandas. Mentorship and Support: Offer one-on-one mentorship to learners, addressing individual doubts and helping them troubleshoot complex problems. Monitor learners progress, provide constructive feedback, and suggest improvement strategies. Assessment and Evaluation: Develop and administer assessments to evaluate learners understanding and skill levels. Analyze test results and provide detailed performance feedback. Domain-Specific Expertise: Explain and demonstrate key AI/ML concepts, such as supervised and unsupervised learning, reinforcement learning, natural language processing (NLP), and computer vision techniques. Guide learners in working with large language models (LLMs) like GPT and BERT, focusing on fine-tuning and deployment. Train learners on deep learning topics, including neural networks, CNNs, RNNs, and transformers. Stay Updated on Trends: Continuously research advancements in AI, ML, Deep Learning, and Python, incorporating cutting-edge techniques into the training materials. Maintain familiarity with emerging technologies like generative AI and explainable AI. Soft Skills and Collaboration: Communicate complex concepts clearly to learners from diverse technical and non-technical backgrounds. Foster an engaging and interactive learning environment, encouraging collaboration among participants. What We Offer Be part of cutting-edge AI projects and work on real-world applications of Machine Learning, Deep Learning, Large Language Models (LLMs), and Computer Vision. Opportunity to stay ahead in the AI revolution by working with the latest tools and technologies like TensorFlow, PyTorch, OpenCV, and Hugging Face. Access to continuous learning resources and mentorship programs to sharpen your expertise and stay updated with emerging trends. Build leadership and communication skills by mentoring learners and engaging with professionals across various industries. Connect with industry experts, aspiring AI professionals, and innovators, giving you a strong professional network. Grow with the company! Be part of our exciting journey as we expand and make an impact in the AI training industry. Enjoy early access to leadership opportunities and the chance to shape the companys future direction. Our Culture & Values Startup Culture - Fast-Paced, Collaborative, and Innovative A place for growth. We believe in nurturing talent and giving everyone the chance to grow professionally and personally We work as a team, supporting and learning from each other. Every voice matters here We trust our team to take ownership of their work and make meaningful contributions. Dynamic startup energy Collaborative leadership Continuous learning