1047 Llm Jobs - Page 17

Role Overview :- Monitor, evaluate, and optimize AI/LLM workflows in production environments. Ensure reliable, efficient, and high-quality AI system performance by building out an LLM Ops platform that is self-serve for the engineering and data science departments. Key Responsibilities:- Collaborate with data scientists and software engineers to integrate an LLM Ops platform (Opik by CometML) for existing AI workflows Identify valuable performance metrics (accuracy, quality, etc) for AI workflows and create on-going sampling evaluation processes using the LLM Ops platform that alert when metrics drop below thresholds Cross-team collaboration to create datasets and benchmarks for new AI workflows Run experiments on datasets and optimize performance via model changes and prompt adjustments Debug and troubleshoot AI workflow issues Optimize inference costs and latency while maintaining accuracy and quality Develop automations for LLM Ops platform integration to empower data scientists and software engineers to self-serve integration with the AI workflows they build Requirements:- Strong Python programming skills Experience with generative AI models and tools (OpenAI, Anthropic, Bedrock, etc) Knowledge of fundamental statistical concepts and tools in data science such as: heuristic and non-heuristic measurements in NLP (BLEU, WER, sentiment analysis, LLM-as-judge, etc), standard deviation, sampling rate, and a high level understanding of how modern AI models work (knowledge cutoffs, context windows, temperature, etc) Familiarity with AWS Understanding of prompt engineering concepts People skills: you will be expected to frequently collaborate with other teams to help to perfect their AI workflows Experience Level 3-5 years of experience in LLM/AI Ops, MLOps, Data Science, or MLE

Key Responsibilities: Architect and implement advanced AI solutions leveraging LLMs (and otheremerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI). Develop and refine AgenticAI systems focusingon planning, memory,tool utilization, and dynamic task critic execution. Engineer and optimize prompt engineering pipelines to achieve superioraccuracy and low latency across diverse applications. Fine-tune and deploy specialized LLMs and AI copilots to transform engineering and business operations. Collaborate with cross-functional teams to deliverproduction-grade solutions that create tangible value. Stay ahead of the curve by integrating emergingGenAI research and state-of-the-art capabilities into practical, real-world systems. Lead projects and mentor junior engineers, contributing to a culture of innovation and growth Required Qualifications: Experience: 3-8 years of hands-on ML/AI/Deep Learning experience, with a strong portfolio of real world application development. Technical Proficiency: Advanced Python skills and extensive experience with leading AI tools and libraries (OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow). Core Knowledge: Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.g., FAISS, Weaviate). Prompt Engineering Mastery: Proven expertise in designing and implementing effective, reusable prompts for complex reasoning, classification, generation, and tool integration tasks across a wide variety of models including open-source solutions. Agentic AI Acumen: Prior experience with autonomous AI agents or multi-agent orchestration is a significant advantage. \ Mindset: A startup-ready attitude - agile, intellectually curious, and hands-on, thriving in fast paced, iterative environments Role & responsibilities

ML Engineer is responsible to discover the information hidden in vast amounts of data and help us make smarter decisions to deliver better products. Your primary focus will be in applying machine learning techniques for data mining and statistical analysis, Text analytics using NLP/LLM and building high quality prediction systems integrated with our products. Job Responsibilities: Building models using best in class ML technology including LLMs. Training/fine tuning models with new/modified training dataset. Selecting features, building, and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods Processing, cleansing, and verifying the integrity of data used for analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Technical skills Mandatory 5 to 10 years of experience as Machine Learning Engineer with strong Python skill. Graduate in Engineering, Technology along with good business skills Good scripting and programming skills in Python Excellent understanding of machine learning techniques and algorithms including knowledge about LLM like GPT, Llama, Claude, or Anthropic models etc. Experience with NLP. Knowledge about applied statistics skills, such as distributions, statistical testing, regression, etc. Basic understanding of NoSQL databases, such as MongoDB, Cassandra. Nice to have Exposure to financial research domain Experience with JIRA, Confluence Understanding of scrum and Agile methodologies Experience with data visualization tools, such as Grafana, power BI, GGplot, etc. Soft skills Oral and written communication skills Good problem solving and negotiation skills Passion, curiosity and attention to detail

We are looking for a junior engineer passionate about Trainee-Generative AI (GenAI) to join our team. In this role, you will assist in designing, prototyping, and deploying GenAI applications using models such as GPT, LLaMA, or other transformer-based architectures. You will work closely with senior engineers, data scientists, and product managers to explore GenAIs potential across various use cases. Key Responsibilities: Support the development of applications using foundation models (e.g., GPT, Claude, Gemini, LLaMA, Mistral). Assist in fine-tuning or prompt-engineering of large language models (LLMs) for specific business use cases. Build and test LLM pipelines using APIs (OpenAI, Hugging Face, Cohere, etc.). Contribute to prompt design, evaluation, and benchmarking of GenAI model outputs. Collaborate on building GenAI-powered chatbots, copilots, summarizers, and content generation tools. Participate in data preparation, cleaning, and formatting for model training and evaluation. Implement simple RAG (Retrieval-Augmented Generation) pipelines under guidance. Contribute to documentation, model evaluation reports, and performance dashboards.

Role & responsibilities AI ML Engineer Location: Bangalore/ Hyderabad Skills: Generative AI, LLM, Python, PyTorch, TensorFlow, Agentic AI

Very Urgent: GenAI Consultant / Sr. GenAI Consultant Company: AurumData Solutions Location: Hyderabad Experience:7 -10Years (2+years in AI) Work type: Work From Office Key skills: GenAI, Python, Data analysis, LLM, TensorFlow, PyTorch, SQL, RAG, NLP, LangChain, LangGraph, SQL etc.. JD for Gen AI Consultant: This job description outlines a role for an AI Specialist who will be responsible for developing and implementing AI solutions across various domains. Here's a breakdown of the key aspects: This position combines traditional machine learning expertise with cutting-edge LLM technologies and practical application development skills. The role requires experience across the full AI development stack, from data management and model fine-tuning to building sophisticated agent-based systems and user-facing applications. Core Responsibilities - Developing AI models and algorithms - Implementing machine learning techniques for data analysis - Creating NLP applications (chatbots, virtual assistants) - Data preprocessing and feature engineering - Model evaluation and optimization - Research and innovation in AI - Cross-functional collaboration - Technical documentation Required Skills - Strong background in machine learning and deep learning - Python programming with frameworks like TensorFlow and PyTorch - Independent project management capabilities - Data science workflow experience - Cloud platform knowledge (AWS, Google Cloud, Azure) - Problem-solving with practical solutions - **Experience with vector databases** - **Knowledge of Large Language Models (LLMs)** - **Implementation of Retrieval-Augmented Generation (RAG) systems** - **Experience with LLM fine-tuning techniques** - **Expertise in fine-tuning LLMs for specific domains/tasks** - **Front-end development skills** for AI application interfaces - **Proficiency with Pydantic** for data validation and settings management - **Experience developing agentic frameworks** for autonomous AI systems - **Familiarity with LangChain** for building LLM applications - **Knowledge of Hugging Face** ecosystem and model hub - **Experience with LangGraph** for building complex, multi-agent systems Qualifications - Bachelor's or Master's in Computer Science, AI, or related fields - Experience in startup environments - Passion for AI applications If you are interested, kindly send your CVs to Madhavi@aurumdatasolutions.com

Were Hiring | Data Science Manager Location: Bangalore Experience: 813 Years Must-Have Skills: • Proven experience as a Data Scientist • Strong Python coding skills • Hands-on with libraries: NumPy, Pandas, Scikit-learn, etc. • Exposure to LLMs & Generative AI • Experience in Project & Team Management

Role Overview We are seeking a highly skilled Senior Data Scientist with a minimum of 5 years of experience to join our Customer Experience Analytics team. The successful candidate will play a pivotal role in building products that enable leadership to extract insights efficiently, fostering data-driven decision-making processes. If you are passionate about leveraging NLP, ML algorithms, and feature engineering to drive business impact and enhance the customer experience, we invite you to join our team at FedEx. What youll be working on Collaborate cross-functionally with various teams to analyze user behavior and usage patterns, extracting actionable insights to enhance customer experience. Utilize advanced statistical techniques, NLP, and ML algorithms to identify opportunities for business problem-solving, leveraging scientific methodologies. Develop and refine predictive models based on historical user data, with a focus on feature engineering and improving machine learning algorithms for production. Design and execute controlled experiments to evaluate the potential impact of new approaches, contributing to data-driven decision-making processes. Provide detailed analysis and reporting on current trends and performance metrics, using NLP techniques for text data and identifying opportunities for improvement. Translate complex data findings into actionable insights for leadership, leveraging NLP outputs and ML algorithms for advanced analytics. Take ownership of end-to-end solution delivery, from problem statement formulation to product implementation, collaborating with other teams as needed. Contribute to the development of solutions and products supporting FedEx's GenAI services, specifically tailored for the Customer Experience vertical. What we are looking for Bachelors degree in computer science, Statistics, Mathematics, or a related field. Advanced degree preferred. Minimum of 5 years of experience in data science, with a focus on customer analytics, NLP, and machine learning. Proficiency in statistical analysis, predictive modeling, NLP techniques, and feature engineering. Any experience with development of GenAI solutions is preferred. Strong programming skills in languages such as Python, with experience in data manipulation and analysis libraries. Demonstrated experience in designing and executing controlled experiments to drive business insights. Excellent communication skills, with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders. Proven track record of delivering end-to-end solutions in a fast-paced, dynamic environment. Experience working with large-scale datasets and distributed computing frameworks is a plus.

Company Description: Maantic Inc is a global strategy and solutions integration firm headquartered in California. Maantic specializes in the implementation of business applications including BPM, CRM, RPA and AI/ML. Maantic's core focus is in Pega, Salesforce, Appian, Robotics Process Automation, ServiceNow and Digital Marketing. Maantic also works with a lot of Product companies helping them in both Engineering and IT. Job Details: Position: AI Software Engineer Experience: 6+ Years Work Mode: Hybrid Location: Hyderabad (HiTech City) Note: Location first preference Hyderabad based but anyone ready to relocate to Hyderabad we can consider (in case of hometown). Gen AI with any frontend and backend technologies experience is must. Any Cloud Experience is must Candidates should be very strong in communication. Generative AI relevant 2+ years experience will be considered Key Responsibilities Engineer well architected, efficient, scalable, stable, and secure web applications and backend services, with an emphasis on APIs and backend services Develop scalable Generative AI systems that can be used across multiple projects and platforms. Stay up-to-date with modern software engineering practices, procedures, and paradigms and apply this knowledge to software Collaborate with an international engineering and product team Experience Bachelor/Master's degree in Computer Science, Computer Engineering, or related field or equivalent experience Atleast 6+ years of job experience in a hands-on role working on front end (React JS, Next JS or similar technologies), backend (Java, .NET), hyperscalers (Google Cloud, Azure, AWS) and have Python experience Experience working with VCS tools such as GIT. Experienced in branching/merging and building CI/CD pipelines. Experience with security protocols such as oAuth, Microsoft Entra ID, SSO, Okta and securing applications using them. Experience to development and deployment of applications using Docker, Kubernetes Experience working with varied integration patterns (REST, SOAP, gRPC, Web Sockets, Batch, Webhooks.). Hands-on experience creating unit test cases, integration test cases, perform code reviews Experience managing version control solutions, static code analysis, and performing code reviews. You have experience with load testing, troubleshooting, and optimizing performance of web services Clear communication and excellent problem-solving skills Enjoy working independently and in a team environment Beneficial Experience Experience using Generative AI software engineering solutions, such as Cursor/Git Hub CoPilot Knowledge of reinforcement learning, natural language processing, and other advanced AI techniques. Experience with cloud-based AI services and IaaC such as Terraform and Ansible. You have experience working in large data-driven services Experience with Generative AI solutions, such as Azure AI Studio, AWS Bedrock, and Hugging Face Experience working on RAG ingestion, evaluation, data cleansing, curation and slack integration.

Role & responsibilities Execute data science projects from start to end. Understand client business problems, define analytical approaches, and develop actionable solutions. Engage directly with stakeholders to gather requirements, present findings, and guide data-driven decisions. Preprocess and analyze structured and unstructured data using statistical approach. Build and deploy predictive models, forecasting solutions, recommendation systems. Collaborate with engineering, product, and business teams to translate insights into outcomes. Communicate results clearly through presentations and storytelling. Preferred candidate profile Graduate degree or higher with courses in programming, econometrics / data science Experience: 3 - 8 years of relevant professional work experience in advanced analytics domain, using statistical modeling and deep learning for business problem solutions. Well-developed Logical Reasoning, Critical Thinking & Problem-Solving abilities. Excellent presentations skills and storytelling capabilities. Self-driven with a collaborative attitude and a passion for delivering business value through data. Strong hands-on experience in Python/R and SQL. Good understanding and Experience with cloud platforms such as Azure, AWS, or GCP. Experience with data visualization tools in python like Seaborn, Plotly. Good understanding of Git concepts. Good experience with data manipulation tools in python like Pandas, Numpy. Must have worked with scikit learn, NLTK, Spacy, transformers. Strong foundation in machine learning algorithms, predictive modeling, and statistical analysis. Good understanding of deep learning concepts, especially in NLP and Computer Vision applications. Proficiency in time-series forecasting and business analytics for functions like marketing, sales, operations, and CRM. Exposure to tools like Mlflow, model deployment, API integration, and CI/CD pipelines. Good to have: Generative AI Experience with text and Image data. Familiarity with LLM frameworks such as LangChain and hubs like Hugging Face. Exposure to vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search or retrieval-augmented generation (RAG). In a changing world, diversity and inclusion are core values for team well-being and performance. At Metyis, we want to welcome and retain all talents, regardless of gender, age, origin or sexual orientation, and irrespective of whether or not they are living with a disability, as each of them has their own experience and identity.

Role & responsibilities What youll be working on Collaborate cross-functionally with various teams to analyze user behavior and usage patterns, extracting actionable insights to enhance customer experience. Utilize advanced statistical techniques, NLP, and ML algorithms to identify opportunities for business problem-solving, leveraging scientific methodologies. Develop and refine predictive models based on historical user data, with a focus on feature engineering and improving machine learning algorithms for production. Design and execute controlled experiments to evaluate the potential impact of new approaches, contributing to data-driven decision-making processes. Provide detailed analysis and reporting on current trends and performance metrics, using NLP techniques for text data and identifying opportunities for improvement. Translate complex data findings into actionable insights for leadership, leveraging NLP outputs and ML algorithms for advanced analytics. Take ownership of end-to-end solution delivery, from problem statement formulation to product implementation, collaborating with other teams as needed. Contribute to the development of solutions and products supporting FedEx's GenAI services, specifically tailored for the Customer Experience vertical. What we are looking for Bachelor’s degree in computer science, Statistics, Mathematics, or a related field. Advanced degree preferred. Minimum of 5 years of experience in data science, with a focus on customer analytics, NLP, and machine learning. Proficiency in statistical analysis, predictive modeling, NLP techniques, and feature engineering. Any experience with development of GenAI solutions is preferred. Strong programming skills in languages such as Python, with experience in data manipulation and analysis libraries. Demonstrated experience in designing and executing controlled experiments to drive business insights. Excellent communication skills, with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders. Proven track record of delivering end-to-end solutions in a fast-paced, dynamic environment. Experience working with large-scale datasets and distributed computing frameworks is a plus.

About this role: Wells Fargo is seeking for a candidate who is responsible for overseeing enterprise data governance, quality and integrity initiatives. The candidate should collaborate with the business and technology partners to ensure the data is accurate, consistent, accessible and aligned with business needs. the role combines deep technical skills, strategic thinking, cross functional leadership and hands-on problem solving. In this role, you will: Organize and lead complex companywide initiatives to ensure that data quality is maintained so that data can effectively support business processes Oversee analysis and reporting in support of regulatory requirements Identify and recommend analysis of data quality or integrity issues Evaluate data quality metrics and data quality audits to benchmark the state of data quality Make decisions in complex and multi-faceted situations requiring solid understanding of data governance standards and procedures Identify new data sources and develop recommendations for assessing the quality of new data Lead project teams and mentor less experienced staff members Recommend remediation of process or control gaps that align to management strategy Serve as relationship manager for a line of business Consult with and provide recommendations to senior management regarding assessments of the current state of data and metadata quality within area of assigned responsibility Represent client in cross-functional groups to develop companywide data governance strategies Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to coordinate and drive collaboration on solution design and remediation execution Required Qualifications: 7+ years of Data Management, Business Analysis, Analytics, or Project Management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Lead efforts through phases of a large enterprise project; requirements, design, implementation, testing, and end-state product management Lead complex data product initiatives, including those that are cross-functional with broad impact, and act as key participant in large-scale planning driving data enablement and capabilities across platforms and utilities Review and analyze complex multi-faceted, larger scale or longer-term data product initiatives that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors to drive data enablement strategies and roadmaps, while adhering to set data governance and standards Make decisions in complex and multi-faceted situations requiring solid understanding of data, analytics, and integration needs of line of business partners to inform prioritization, roadmap, and architecture design, that influence and lead broader work team to meet deliverables and drive new initiatives Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to ensure data product solutions are built for optimal performance and design analytics applications across multiple platforms, resolve data product issues, and achieve goals; may lead projects, teams or serve as a peer mentor Provide strategic input on new use case intake, prioritization, product roadmap definition, and other critical business processes Manage complex datasets continuously focusing on the consumers of the data and their business needs, while adhering to set data governance Create and maintain data product roadmaps throughout the data product life cycle with detailed specifications, requirements, and flows for data capabilities Design and maintain innovative data products, enabling data availability for data intelligence, analytics, and reporting Serve as a strategic liaison between data management, product teams, data engineering, and architecture teams throughout the data product life cycle Skills: SQL - Teradata, Snowflake Python, Regression & Clustering, Alteryx & LLM Job Expectations: Lead development and implementation of data management strategies across business units. Ensure consistent data definition and usage across systems. Mentor and guide data analysts, enforcing best practices in data handling Collaborate with data engineers and architects to optimize data flow and storage. Oversee processes for data profiling, validation, cleansing and enrichment Identify, investigate and resolve data quality issues through root cause analysis Support data integration efforts and data architecture review

Job Overview Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done. Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

We are looking for a Machine Learning Engineer with expertise in MLOps (Machine Learning Operations) or LLMOps (Large Language Model Operations) to design, deploy, and maintain scalable AI/ML systems. You will work on automating ML workflows, optimizing model deployment, and managing large-scale AI applications, including LLMs (Large Language Models) , ensuring they run efficiently in production. Key Responsibilities: Design and implement end-to-end MLOps pipelines for training, validation, deployment, monitoring, and retraining of ML models. Optimize and fine-tune large language models (LLMs) for various applications, ensuring performance and efficiency. Develop CI/CD pipelines for ML models to automate deployment and monitoring in production. Monitor model performance, detect drift , and implement automated retraining mechanisms. Work with cloud platforms ( AWS, GCP, Azure ) and containerization technologies ( Docker, Kubernetes ) for scalable deployments. Implement best practices in data engineering , feature stores, and model versioning. Collaborate with data scientists, engineers, and product teams to integrate ML models into production applications. Ensure compliance with security, privacy, and ethical AI standards in ML deployments. Optimize inference performance and cost of LLMs using quantization, pruning, and distillation techniques . Deploy LLM-based APIs and services, integrating them with real-time and batch processing pipelines. Key Requirements: Technical Skills: Strong programming skills in Python, with experience in ML frameworks ( TensorFlow, PyTorch, Hugging Face, JAX ). Experience with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker, Airflow). Deep understanding of LLM architectures , prompt engineering, and fine-tuning. Hands-on experience with containerization (Docker, Kubernetes) and orchestration tools . Proficiency in cloud services (AWS/GCP/Azure) for ML model training and deployment. Experience with monitoring ML models (Prometheus, Grafana, Evidently AI). Knowledge of feature stores (Feast, Tecton) and data pipelines (Kafka, Apache Beam). Strong background in distributed computing (Spark, Ray, Dask) . Soft Skills: Strong problem-solving and debugging skills. Ability to work in cross-functional teams and communicate complex ML concepts to stakeholders. Passion for staying updated with the latest ML and LLM research & technologies . Preferred Qualifications: Experience with LLM fine-tuning , Reinforcement Learning with Human Feedback ( RLHF ), or LoRA/PEFT techniques . Knowledge of vector databases (FAISS, Pinecone, Weaviate) for retrieval-augmented generation ( RAG ). Familiarity with LangChain, LlamaIndex , and other LLMOps-specific frameworks. Experience deploying LLMs in production (ChatGPT, LLaMA, Falcon, Mistral, Claude, etc.) .

Job Description: Role Overview We are seeking a highly skilled AI Engineer with 8-12 years of experience to lead the development of Generative AI (GenAI) and Machine learning solutions for internal projects. This role requires a self-driven leader with exceptional communication, strategic thinking, and expertise in data analytics and visualization to deliver innovative GenAI tools tailored to internal team needs while driving cross-functional collaboration. Key Responsibilities GenAI Development: Design and develop advanced GenAI models (e.g., LLMs, DALL E models) and AI Agents to automate internal tasks and workflows. Exposure to LLMs: Utilize Azure Open AI APIs, experience on models like GPT4o, O3 , llama3 Enhance the existing R AG based application: In depth understanding of stages of RAG - chunking, retrieval etc. Cloud Deployment: Deploy and scale GenAI solutions on Azure Cloud services (e.g., Azure Function App) for optimal performance. In depth understanding of ML models like linear regression, random forest, decision trees. In depth understanding on clustering and supervised models. AI Agent Development: Build AI agents using frameworks like LangChain to streamline internal processes and boost efficiency. Data Analytics : Perform advanced data analytics to preprocess datasets, evaluate model performance, and derive actionable insights for GenAI solutions. Data Visualization: Create compelling visualizations (e.g., dashboards, charts) to communicate model outputs, performance metrics, and business insights to stakeholders. Stakeholder Collaboration: Partner with departments to gather requirements, align on goals, and present technical solutions and insights effectively to non-technical stakeholders. Model Optimization: Fine-tune GenAI models for efficiency and accuracy using techniques like prompt engineering, quantization, and RAG (Retrieval-Augmented Generation). LLMOps Best Practices: Implement GenAI-specific MLOps, including CI/CD pipelines (Git, Azure DevOps) Leadership: Guide cross-functional teams, mentor junior engineers, and drive project execution with strategic vision and ownership. Helicopters, strategic Thinking: Develop innovative GenAI strategies to address business challenges, leveraging data insights to align solutions with organizational goals. Self-Driven Execution: Independently lead projects to completion with minimal supervision, proactively resolving challenges and seeking collaboration when needed. Continuous Learning: Stay ahead of GenAI, analytics, and visualization advancements, self-learning new techniques to enhance project outcomes. Required Skills & Experience : 8-12 years in AI/ML development, with at least 4 years focused on Generative AI and AI agent frameworks. Education: BTech/BE in Computer Science, Engineering, or equivalent (Masters or PhD in AI/ML is a plus). Programming: Expert-level Python proficiency, with deep expertise in GenAI libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, Open AI SDK) and data analytics libraries (e.g., Pandas, NumPy), sk-learn. Mac Data Analytics: Strong experience in data preprocessing, statistical analysis, and model evaluation to support GenAI development and business insights. Data Visualization: Proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau) to create dashboards and reports for stakeholders. Azure Cloud Expertise: Strong experience with Azure Cloud services (e.g., Azure Function App, Azure ML, serverless) for model training and deployment. GenAI Methodologies : Deep expertise in LLMs, AI agent frameworks, prompt engineering, and RAG for internal workflow automation. Deployment : Proficiency in Docker, Kubernetes, and CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production-grade GenAI systems. LLMOps: Expertise in GenAI MLOps, including experiment tracking (e.g., Weights & Biases), automated evaluation metrics (e.g., BLEU, ROUGE), and monitoring. Communication: Exceptional verbal and written skills to articulate complex GenAI concepts, analytics, and visualizations to technical and non-technical stakeholders. Strategic Thinking: Ability to align AI solutions with business objectives, using data-driven insights to anticipate challenges and propose long-term strategies. Problem-Solving : Strong analytical skills with a proactive, self-starter mindset to independently resolve complex issues. Collaboration: Collaborative mindset to work effectively across departments and engage colleagues for solutions when needed. Preferred Skills Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data science

Requirements: Bachelors/Master’s degree in Computer Science or equivalent. A minimum of 2-3 years of hands-on experience in Python software development with a focus on modular, scalable, and efficient coding for AI/LLM-based applications. Experience developing and maintaining RESTful APIs using FastAPI and interfacing with relational databases. Experience in implementing LLMs (OpenAI, Azure) using vector databases, text embedding, and RAG. Hands-on experience with cloud platforms (AWS, Azure, GCP) and docker for AI deployment and scaling. Strong Git skills for version control and collaborative development. Ability to adjust and thrive in a fast-paced environment with changing priorities. Strong analytical and problem-solving skills. Familiarity with data visualization tools such as Strategy preferred.

Job Overview We are seeking a highly experienced Senior AI Developer with extensive expertise in the latest generative AI (GenAI), agentic AI, and other cutting-edge artificial intelligence technologies. The ideal candidate has a proven track record of designing and deploying advanced AI solutions in dynamic, data-intensive environments. This role is perfect for an innovative thinker who thrives in fast-paced settings and is eager to push the boundaries of AI technology. ________________________________________ Key Responsibilities Advanced AI Development: Architect, develop, and implement AI models and systems, with a strong focus on generative and agentic AI. Leverage state-of-the-art algorithms and frameworks to build scalable and high-performance AI applications. Research & Innovation: Stay abreast of the latest trends and breakthroughs in AI, particularly in GenAI and agentic AI. Experiment with novel approaches and techniques to drive innovation and enhance product capabilities. Collaboration & Integration: Work closely with cross-functional teamsincluding data scientists, software engineers, and product managers—to integrate AI solutions into existing systems. Ensure seamless data flow and optimal performance across various platforms. Code Quality & Mentorship: Write robust, clean, and maintainable code. Lead technical discussions, perform code reviews, and mentor junior developers, fostering a culture of continuous learning and excellence. Performance Optimization & Scalability: Optimize AI models for efficiency and scalability. Address performance bottlenecks and continuously monitor system performance to ensure reliability and accuracy. ________________________________________ Required Qualifications Experience: Extensive industry experience in AI development, with a strong portfolio that demonstrates proficiency in generative AI and agentic AI applications. Technical Skills: AI Frameworks & Libraries: Hands-on experience with modern AI frameworks (e.g., TensorFlow, PyTorch) and familiarity with emerging generative AI platforms. Programming Languages: Proficiency in Python, with exposure to additional languages like Rust or C++ considered a plus. Data Management: Expertise in handling large-scale, data-intensive environments and designing efficient data pipelines. Core Competencies: Strong analytical and problem-solving skills with the ability to translate complex business requirements into technical solutions. Excellent communication skills for effective collaboration across diverse teams. Familiarity with Agile methodologies and best practices in software development. ________________________________________ Preferred Qualifications Advanced degrees (Master’s/Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience with cloud-based AI solutions and infrastructure (e.g., AWS, Azure, Google Cloud). Proven track record of contributing to AI research publications or patents in the field of generative and agentic AI. Knowledge of ethical AI practices and ensuring model fairness, transparency, and accountability.

Work shift Timings 11 AM to 8 PM Notes : Overall 10-14 yrs. of exp + Full time Undergraduation Must have Strong experience in Data Science for atleast 6+ yrs. Hands on experience in Machine learning & Deep learning Should have worked in LLM, RAG, SFT, CPT Models Should have exp in Cloud based tools for Machine learning Operations (Deployment) Azure Databricks, AWS Sagemaker Should have exp in Frameworks like Flask, Fast API Team management is compulsory Job Title: Manager - Government and Public Services Enabling Areas (GPS EA). The Team: GPS GSi The Role: Senior Data Scientist The Team: Do you have a strong background in machine learning and deep learning? Are you interested in utilizing your data science skills and collaborating with a small team in a fast-paced environment to achieve strategic mission goals? If so, Deloitte has an exciting opportunity for you! As a member of our GPS GSi group, you will play a crucial role in the development and maintenance of our data science and business intelligence solutions. This role will specialize in assisting with machine learning, deep learning, and generative AI initiatives that will be utilized by Enabling Area professionals to enhance and expedite decision-making. You will provide expertise within and across business teams, demonstrate the ability to work independently / as a team, and apply problem-solving skills to resolve complex issues. Work you will do. Technology: • Deliver exceptional client service. Maximizes results and drives high performance from people while fostering collaboration across businesses and geographies • Interfacing with business customers and leadership to gather requirements and deliver complete Data Engineering, Data Warehousing, and BI solutions. • Design, train, and deploy machine learning and deep learning models to AWS, Databricks, and Dataiku platforms. • Develop, design, and/or advise on Large Language Model (LLM) solutions for enterprise-wide documentation (e.g., Retrieval-Augmented Generation (RAG), Continued Pre-training (CPT), Supervised Fine-tuning (SFT), etc.) • Utilize Machine Learning Operations (MLOps) pipelines, including knowledge of containerization (Docker) and CI/CD for training and deploying models. • Maintain structured documentation of project development stages, including the utilization of GitHub and/or Jira for version control and project management. • Demonstrate effective communication skills with the ability to provide expertise and break down complex analytical solutions to explain to clients. • Remain current with latest industry trends and developments in data science and/or related fields, with the ability to learn new skills and knowledge to advance the skillset of our Data Science team. • Apply thorough attention to detail, and carefully review data science solutions for accuracy and quality. Leadership: • Develop high-performing teams by providing challenging and meaningful opportunities, and acknowledge their contributions to the organization's success. • Establish the team's strategy and roadmap, prioritizing initiatives based on their broader business impact. • Demonstrate leadership in guiding both US and USI teams to deliver advanced technical solutions across the GPS practice. • Serve as a role model for junior practitioners, inspiring action and fostering positive behaviors. • Pursue new and challenging initiatives that have a positive impact on our Practice and our personnel. • Establish a reputation as a Deloitte expert and be acknowledged as a role model and senior member by client teams. • Support and participate in the recognition and reward of junior team members. People Development: • Actively seek, provide, and respond to constructive feedback. • Offer development guidance to the GSi team, enhancing their people, leadership, and client management skills. • Play a pivotal role in recruitment and the onboarding of new hires. • Engage in formal performance assessment activities for assigned staff and collaborate with Practice leadership to address and resolve performance issues. • Serve as an effective coach by helping counselees identify their strengths and opportunities to capitalize on them. • Foster a "One Team" mindset among US and USI team members. Qualifications: Required/Preferred: • Bachelor's degree, preferably in Management Information Systems, Computer Science, Software Engineering, or related IT discipline • Minimum of 10+ years of relevant experience with data science technologies and analytics advisory or consulting firms. • Strong knowledge of LLMs and RAG. • Familiarity with AWS, Databricks, and/or Dataiku platforms. • Working knowledge of MLOps, including familiarity with containerization (e.g., Docker). • Excellent troubleshooting skills and the ability to work independently. • Strong organizational skills, including clear documentation of projects and ability to write clean code. • Familiarity with agile project methodology and/or project development lifecycle. • Experience with GitHub for version control. • Excellent communication and presentation skills, with the ability to explain complex data science concepts to non-technical audiences. • Ability to complete work in an acceptable timeframe and manage a variety of detailed tasks and responsibilities simultaneously and with accuracy to meet deadlines, goals, and objectives and satisfy internal and external customer needs related to the job. • Extensive experience with MLOps and associated serving frameworks (i.e., Flask, FastAPI, etc.) and orchestration pipelines (e.g., Sage Maker Pipelines, Step Functions, Metaflow, etc.). • Extensive experience working with open source LLMs (e.g., serving via TGI / vLLM, performing CPT and/or SFT, etc.). • Experience using various AWS Services (e.g., Textract, Transcribe, Lambda, etc.). • Proficiency in basic front-end web development (e.g., Streamlit). • Knowledge of Object-Oriented Programming (OOP) concepts. • At least 3-4 years of people management skills are required. • Work Location: Hyderabad Timings: 2 PM 11PM How you’ll grow At Deloitte, we’ve invested a great deal to create a rich environment in which our professionals can grow. We want all our people to develop in their own way, playing to their own strengths as they hone their leadership skills. And, as a part of our efforts, we provide our professionals with a variety of learning and networking opportunities— including exposure to leaders, sponsors, coaches, and challenging assignments—to help accelerate their careers along the way. No two people learn in exactly the same way. So, we provide a range of resources including live classrooms, team-based learning, and eLearning. DU: The Leadership Center in India, our state-of-the-art, worldclass learning Center in the Hyderabad offices is an extension of the Deloitte University (DU) in Westlake, Texas, and represents a tangible symbol of our commitment to our people’s growth and development. Explore DU: The Leadership Center in India Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Deloitte’s culture Our positive and supportive culture encourages our people to do their best work every day. We celebrate individuals by recognizing their uniqueness and offering them the flexibility to make daily choices that can help them to be healthy, centered, confident, and aware. We offer well-being programs and are continuously looking for new ways to maintain a culture that is inclusive, invites authenticity, leverages our diversity, and where our people excel and lead healthy, happy lives. Learn more about Life at Deloitte. Corporate citizenship Deloitte is led by a purpose: to make an impact that matters. This purpose defines who we are and extends to relationships with our clients, our people and our communities. We believe that business has the power to inspire and transform. We focus on education, giving, skill-based volunteerism, and leadership to help drive positive social impact in our communities. Learn more about Deloitte’s impact on the world.

Responsibilities: * Develop computer vision models using generative AI techniques. * Optimize model performance through LLM integration. * Collaborate with cross-functional teams on project delivery. Share your resumes to sruthi.gali@liftu.tech

Key Responsibilities Technical Development: Design and develop backend services using Java, Spring Boot, and related frameworks. Write clean, modular, and testable code following best practices. Participate in technical design discussions and peer reviews. Contribute to the evolution of our microservices architecture. Code Quality & Testing: Implement and maintain unit and integration tests (e.g., using JUnit, Postman). Contribute to CI/CD pipelines and ensure code is production-ready. Collaborate with QA to support functional and end-to-end test coverage. Collaboration & Agile Execution: Work closely with product managers, senior engineers, and designers to translate requirements into technical deliverables. Participate in Agile ceremonies including sprint planning, retrospectives, and demos. Provide accurate effort estimates and deliver to sprint commitments. Learning & Tooling: Leverage modern tools, including LLMs and AI utilities, to streamline development and improve productivity. Continuously explore new technologies and propose improvements to systems or processes. Skills & Qualifications Must-Have Skills: 5+ years of experience in backend development, primarily using Java and Spring Boot. Strong understanding of RESTful APIs, microservices, and design principles. Experience with version control (Git), build tools (e.g., Maven/Gradle), and CI/CD workflows. Exposure to Agile development and testing frameworks like JUnit or Postman. Good problem-solving and debugging skills. Nice-to-Have Skills: Exposure to frontend technologies (e.g., basic React or Angular) is a plus. Experience with containerization tools like Docker. Awareness of cloud platforms such as AWS or GCP. Understanding of secure development and performance tuning.

Were Hiring: Machine Learning Developer | Noida (Sector 90) Are you ready to accelerate your ML career at a fast-growing B2B SaaS startup? Join a dynamic team that's solving real-world problems with cutting-edge machine learning technologies! Role: Machine Learning Developer Experience: 3.5 to 5 Years Location: Sector 90, Noida Work Mode: 5 Days | Work From Office Notice Period: Immediate to 30 Days Key Responsibilities: Develop and deploy scalable machine learning models Design robust data and AI pipelines Optimize ML workflows for efficiency and performance Maintain and retrain production models as needed What We’re Looking For: Strong Python, PyTorch, Langchain & SQL skills Hands-on with Spark, Dask, Airflow, or Dagster Experience with cloud platforms: AWS, GCP, or Azure Familiarity with MLOps tools: MLflow, Kubeflow, Docker, Kubernetes Bachelor’s/Master’s in CS, AI, Data Science, or related field Interested in or know someone great? Send your resume to gautam@mounttalent.com.

Fresher or 3+ years of experience in AI/ML development with a focus on Generative AI and LLMs. Design, develop, and implement AI/ML models, including Generative AI and LLM-based solutions.

Looking for candidates from Premium institutes education background. Hands on Exp with AI ML, Gen AI - LLM, NLP, Lang chain

Use GPT API or Llama to develop custom frameworks for investment management alternate data analysis Use Orchestration tools like N8n for document ingestion Setup on cloud or private using Coreweave Lead Machine Learning and UI Engineers Required Candidate profile Strong proficiency in Python and frameworks like TensorFlow or PyTorch. 2+ years of experience in GenAI and LLMs Experience with VectorDB, documentation ingestion workflows etc.

Role & responsibilities We are looking for Data Scientist position permanent position with US MNC for Gurgaon location. Job Posting Title: Data Scientist What does a Data Scientist do? As a data scientist, you will be responsible for analyzing and interpreting complex data sets to identify patterns and insights. You will be developing data models and algorithms to support the project needs. Implement data validation strategies to ensure high data quality. Collaborate with AI/ML engineers to integrate data models into the conversion engine system. Present findings and recommendations to stakeholders and management. Not being afraid to fail fast is one of the essential tools an NL Data Scientist can have in the cutting-edge technology market. What you will do: Develop AI-Driven Data Conversion Application: Utilize AI technologies to develop a comprehensive data conversion application. Data Mapping: Implement AI algorithms for accurate data mapping from source to target. Code Generation: Automate code generation using AI models. Data Validation: Apply AI-driven validation techniques to ensure data integrity and quality. Code Conversion: Facilitate seamless code conversion using AI algorithms. Collaboration: Work with data engineers, software developers, AI solution engineers, and business analysts to integrate the data conversion application. Monitor and Troubleshoot: Continuously monitor and troubleshoot the AI-driven application to ensure optimal functionality. Documentation: Maintain detailed documentation of methodologies and processes used in the application development. Stay Updated with Technologies: Keep up-to-date with the latest AI, data science, and data conversion technologies to enhance the application. What you will need to have: Bachelors or Masters Degree in Data Science, Computer Science, Artificial Intelligence, or a related field. Proficiency in Programming Languages such as Python, SQL, and other relevant languages. Experience with AI/ML Frameworks like TensorFlow, PyTorch, or similar. Knowledge of Data Mapping Techniques: Experience with AI-driven tools and methodologies for data mapping.• Strong Code Generation Skills: Experience in developing AI models for automating code generation. Experience with Data Validation: Implementing AI-based validation techniques. Familiarity with Code Conversion: Understanding AI algorithms for code conversion. Experience with Databases like SQL Server and MongoDB. Collaboration Skills: Ability to work effectively with cross-functional teams. Problem-Solving Skills: Strong ability to identify issues and develop creative solutions. Attention to Detail: Ensure accuracy and reliability of data conversions. 5+ Years of Relevant Experience in data science or a related field. Willingness to Fail Fast and learn from mistakes in the fast-paced technology market. Preferred qualifications for consideration: Experience in the Financial Services Industry and an understanding of compliance standards. Certification in Data Science or AI/ML. Experience with Master data management, Data Wrangling and ETL Processes. Familiarity with DevOps Tools like Jira, Confluence, and BitBucket. Experience with data and AI/ML Technologies: Such as NLP/NLU, Azure Cognitive Services, Azure Synapse Analytics, Azure data bricks and Azure ML service. Previous Experience Delivering AI Solutions for complex data or conversions: Seamless Data Schema Conversion, AI-Driven Data Validation for Migration Accuracy, Intelligent Code Generation for Data Transformation Scripts , Historical Data Transformation and Archiving, Intelligent Error Detection and Correction, AI-Augmented Data Reconciliation