1047 Llm Jobs - Page 27

Role & responsibilities ole Overview As an AI Voice & LLM Integration Developer, you will play a pivotal role in building and optimizing Your work will focus on: • Integrating GPT's ASR (speech-to-text) and TTS (text-to-speech) APIs into our platform. • Handling real-time voice streaming from VoIP/SIP systems. • Optimizing low-latency communication between AI models and telephony platforms (e.g., FreeSWITCH, WebRTC). • Supporting PBX call routing & handoWs with AI agents. • Ensuring high-quality, natural-sounding AI-driven voice interactions. Key Responsibilities Design and develop real-time voice processing pipelines for AI-driven conversations. • Integrate OpenAI's Whisper (ASR) and TTS APIs with VoIP and WebRTC systems. • Develop low-latency audio streaming middleware between telephony providers(Telnyx, Bandwidth) and GPT. • Work with SIP and WebRTC to ensure seamless audio transmission. • Implement PBX call routing and AI handoW mechanisms (e.g., transferring AI-handled calls to human agents). • Optimize AI voice latency and response times for a real-time, natural experience. • Collaborate with VoIP engineers to integrate AI capabilities into SIP-based systems. • Design APIs to manage AI-driven IVR workflows and customer interactions. • Ensure compliance with telephony regulations (e.g., STIR/SHAKEN, call recording laws). • Monitor system performance and implement scalability strategies for voice interactions. Required Qualifications AI & LLM Integration o Experience integrating GPT APIs (ChatGPT, Whisper, TTS engines) for voice applications. o Understanding of real-time AI voice processing and conversational AI workflows. Voice & Audio Streaming Experience working with low-latency, real-time audio streaming. o Familiarity with WebRTC, SIP/RTP, and VoIP streaming. Programming & Middleware Development Proficiency in Python, Node.js, or Go for API and middleware development. o Experience developing RESTful APIs and real-time streaming solutions. VoIP & Telephony Knowledge Familiarity with SIP, FreeSWITCH, Asterisk, or other PBX platforms. o Experience working with SIP trunking providers (Telnyx, Bandwidth, Flowroute, etc.). Performance & Optimization Ability to reduce latency in AI-driven conversations. o Experience with audio codec optimization (G.711, Opus, etc.). One or more of the following additional qualifications: Experience with STT/ASR models beyond GPT (Google Speech-to- Text, Deepgram, Kaldi). o Background in signal processing or audio engineering. o Familiarity with cloud-based voice solutions (AWS Connect, Twilio Voice, Dialogflow CX). o Knowledge of containerization (Docker, Kubernetes) for scaling AI voice workloads. o Experience with multi-tenant architectures for voice AI.

Python with AI ML / LLM Python Full stack - Python(Backend) + Angular / React )(Front End) + AI ML / LLM

Role & responsibilities We are looking for Senior Gen AI Engineer permanent position with MNC company for Remote. Preferred candidate profile Senior Gen AI Engineer GenAI / ML (Python, Langchain) Full Time Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities: Design, develop, and deploy chatbots and voice bots utilizing leading Conversational AI platforms such as Microsoft Bot Framework, Google CCAI, and Dialogflow CX. Craft clean, efficient, and maintainable code adhering to industry best practices and standards. Develop custom components and tools to optimize the functionality and performance of our chatbot ecosystem. Collaborate closely with developers, designers, and other stakeholders to meet project requirements and user expectations. Leverage natural language processing (NLP), LLM, and machine learning (ML) techniques, including TTS, STT, and SSML, to enable our chatbots to comprehend and respond intelligently to user inputs. Integrate chatbot systems seamlessly with backend systems, databases, and APIs to facilitate smooth data exchange and interactions. Investigate and resolve complex technical issues by analysing logs and debugging code for continuous improvement. Stay ahead of the curve by keeping up-to-date with the latest trends and advancements in chatbot development. Preferred candidate profile: 4+ years of hands-on experience with the Google Cloud Contact Center AI Bot framework. Proficient in Natural Language Processing (NLP), Natural Language Understanding (NLU), Machine Learning (ML), and Conversational AI. Extensive experience with the new LLM (playbook) feature in Dialogflow CX, as well as traditional Dialogflow CX functionalities. Solid understanding of Google as a Software-as-a-Service platform. Experience with Azure Composer Bots. Proven troubleshooting and analytical skills in complex, distributed environments. Familiarity with SQL and experience working with relational databases. Experience integrating web services into applications. Proficient in Agile and Scrum development methodologies. Bachelors degree in a technology-related field or equivalent experience.

Job Description : As an LLMOps Engineer, you will play a crucial role in the deployment, maintenance, and optimization of large language models (LLMs). Your responsibilities will span the entire lifecycle of LLMs, from initial deployment to ongoing operations, ensuring optimal performance, scalability, and reliability. Key Responsibilities : LLM Deployment and Integration - Deploy and integrate large language models into production environments, ensuring seamless integration with existing systems and applications. Infrastructure Planning and Scaling - Collaborate with cross-functional teams to plan and design the infrastructure required for LLM deployment. Implement scalable solutions to accommodate growing data volumes and user loads. Automation of Deployment Processes - Develop and maintain automation scripts and tools for efficient deployment, scaling, and versioning of LLMs. Streamline deployment processes to minimize downtime. Continuous Monitoring and Alerting - Implement monitoring systems to track LLM performance metrics. Set up alerts for potential issues and respond promptly to ensure uninterrupted service. Performance Monitoring and Optimization - Monitor the performance of LLMs in real-time, conduct regular assessments, and implement optimizations to enhance efficiency and responsiveness. Fault Tolerance and Disaster Recovery - Design and implement fault-tolerant systems for LLMs, incorporating strategies such as redundancy, sharding, and replication. Develop and maintain disaster recovery plans. Security Measures Implementation - Implement robust security measures to safeguard LLMs and associated data. Ensure compliance with data security regulations and industry standards. Collaboration with NLP Engineers and Data Scientists - Collaborate with NLP (Natural Language Processing) engineers and data scientists to understand model requirements and implement necessary infrastructure adjustments. Skills & Tools Infrastructure as Code (IaC) - Experience with IaC tools such as Terraform or Ansible for automating infrastructure provisioning. Containerization and Orchestration - Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for managing LLM deployments. Cloud Platforms - Familiarity with cloud platforms such as AWS (Bedrock), Azure, or GCP, and experience in deploying and managing applications in a cloud environment. Monitoring and Logging Tools - Knowledge of monitoring tools (e.g., Prometheus, Grafana) and logging systems (e.g., ELK stack) for real-time performance monitoring and analysis. Security Measures - Understanding of security guardrails using tools like LLM Guard and familiarity of how to mask / redact / obfuscate sensitive data, protect the input and output of toxic and harmful content to / from LLMs and understand the performance implications of the same. Scripting and Automation - Proficient in scripting languages such as Python, Shell, or similar, and experience in automating deployment and maintenance processes.

Job Description : As a Data Engineer for our Large Language Model Project, you will play a crucial role in designing, implementing, and maintaining the data infrastructure. Your expertise will be instrumental in ensuring the efficient flow of data, enabling seamless integration with various components, and optimizing data processing pipelines. 5+ years of relevant experience in data engineering roles. Key Responsibilities : Data Pipeline Development - Design, develop, and maintain scalable and efficient data pipelines to support the training and deployment of large language models. Implement ETL processes to extract, transform, and load diverse datasets into suitable formats for model training. Data Integration - Collaborate with cross-functional teams, including data scientists and software engineers, to integrate data sources and ensure the availability of relevant and high-quality data. Implement solutions for real-time data processing and integration, fostering model development agility. Data Quality Assurance - Establish and maintain robust data quality checks and validation processes to ensure the accuracy and consistency of datasets. Troubleshoot data quality issues, identify root causes, and implement corrective measures. Infrastructure Management - Work closely with DevOps and IT teams to manage and optimize the data storage infrastructure, ensuring scalability and performance. Implement best practices for data security, access control, and compliance with data governance policies. Performance Optimization - Identify bottlenecks and inefficiencies in data processing pipelines and implement optimizations to enhance overall system performance. Continuously monitor and evaluate system performance metrics, making proactive adjustments as needed. Skills & Tools Programming Languages - Proficiency in languages such as Python for building robust data processing applications. Big Data Technologies - Experience with distributed computing frameworks like Apache Spark, Databricks & DBT for large-scale data processing. Database Systems - In-depth knowledge of both relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., Vector databases, MongoDB, Cassandra etc). Data Warehousing - Familiarity with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake. ETL Tools - Hands-on experience with ETL tools like Apache NiFi, Talend, or Apache Airflow. Knowledge of NLP will be an added advantage. Cloud Services - Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying and managing data infrastructure. Problem Solving - Analytical mindset with a proactive approach to identifying and solving complex data engineering challenges.

Requirements: Bachelors or Master’s degree in Computer Science, Statistics, Mathematics, or a related field. Proficiency in Python, R, or a similar programming language. Experience with SQL and data querying from relational databases. Strong foundation in statistics, machine learning, and data modeling. Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Excellent problem-solving and communication skills.

Amlgo Labs is Hiring | 2 Exciting Roles Available! Location: Gurugram (Hybrid) | Job Type: Full-Time Company Website: https://amlgolabs.com/ Position 1: Junior AI Engineer (Fresher LLMs & Generative AI Focus) Experience: 01 Year | Department: Artificial Intelligence / R&D About the Role: Join our cutting-edge AI team working on Large Language Models (LLMs), Generative AI, and automation solutions. Ideal for recent graduates passionate about machine learning, natural language processing, and prompt engineering. Key Responsibilities: Work with LLMs (e.g., OpenAI, Hugging Face) for development, fine-tuning, and integration Design effective prompts to optimize model performance Assist in deploying generative AI applications (text/code/image) Build Python-based AI/ML pipelines and evaluate models Collaborate with data teams for dataset management and preprocessing Monitor model behavior in production environments Document experiments, results, and technical workflows Required Qualifications: Bachelors in CS, Engineering, Data Science, or related field 01 year experience in AI/ML or relevant project work Proficiency in Python and libraries (NumPy, pandas, scikit-learn, matplotlib) Basic ML understanding and exposure to LLMs (GPT, LLaMA, etc.) Familiarity with Hugging Face, OpenAI API is a plus Awareness of ETL/data engineering practices Position 2: Full Stack Developer Experience: 0-1 Year | Department: Software Development About the Role: We are seeking a driven Full Stack Developer to build robust, scalable, and user-friendly web applications. You will work on both frontend and backend development, ensuring seamless performance from code to deployment. Key Responsibilities: Develop dynamic UIs using React.js, Next.js, TypeScript, Tailwind CSS, HTML/CSS Create backend services and RESTful APIs with Node.js and Python Work with MongoDB for NoSQL database management Manage deployments using Docker, VPS, Linux, and Nginx Collaborate cross-functionally to build high-quality solutions Conduct code reviews and continuously improve development practices Debug across various environments and optimize application performance Required Skills: Solid knowledge of JavaScript and TypeScript Experience in React.js, Next.js, Tailwind CSS, HTML, CSS Hands-on experience with Node.js and Python backend Familiarity with MongoDB and cloud/server deployments Understanding of RESTful API principles and modern dev tools Strong analytical and debugging skills About Us: Amlgo Labs is building the next generation of AI-driven solutions, with a focus on Large Language Models (LLMs), Generative AI, and intelligent automation. We're seeking curious and motivated individuals who want to work at the cutting edge of AI.

Job Responsibility: Products.looking for a data scientist who will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver AI/ML based Enterprise Software Products. • Develop solutions related to machine learning, natural language processing and deep learning & Generative AI to address business needs. • Your primary focus will be in applying Language/Vision techniques, developing llm based applications and building high quality prediction systems. • Analyze Data: Collaborate with cross-functional teams to understand data requirements and identify relevant data sources. Analyze and preprocess data to extract valuable insights and ensure data quality. • Evaluation and Optimization: Evaluate model performance using appropriate metrics and iterate on solutions to enhance performance and accuracy. Continuously optimize algorithms and models to adapt to evolving business requirements. • Documentation and Reporting: Document methodologies, findings, and outcomes in clear and concise reports. Communicate results effectively to technical and non-technical stakeholders. Work experience background required: • Experience building software from the ground up in a corporate or startup environment. Essential skillsets required: • 3-6 years experience in software development • Educational Background: Strong computer science and Math/Statistics • Experience with Open Source LLM and Langchain Framework and and designing efficient prompt for LLMs. • Proven ability with NLP and text-based extraction techniques. • Experience in Generative AI technologies, such as diffusion and/or language models. • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. • Familiarity with cloud computing platforms such as GCP or AWS. Experience to deploy and monitor model in cloud environment. • Experience with common data science toolkits, such as NumPy, Pandas etc • Proficiency in using query languages such as SQL • Good applied statistics skills, such as distributions, statistical testing, regression, etc. • Experience working with large data sets along with data modeling, language development, and database technologies • Knowledge in Machine Learning and Deep Learning frameworks (e.g., TensorFlow, Keras, Scikit-Learn, CNTK, or PyTorch), NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. • Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. • Excellent verbal and written communication skills

Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities: Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications: Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelors Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles.

Job Summary: We are seeking a highly skilled and creative AI ML Engineer with deep expertise in artificial intelligence, natural language processing, and prompt design for large language models (LLMs). This role is crucial in crafting, optimizing, and scaling interactions with advanced AI systems to improve performance, user experience, and business outcomes across various applications. --- Key Responsibilities: Design, test, and refine prompts to optimize performance of LLMs such as GPT-4, Claude, Gemini, and open-source models. Collaborate with cross-functional teams (product, design, engineering, marketing) to develop AI-driven features and tools. Conduct rigorous experimentation and benchmarking of prompts and AI outputs for accuracy, safety, and usability. Automate prompt workflows and integrate prompt chains with APIs and tool stacks. Fine-tune models or build retrieval-augmented generation (RAG) pipelines when needed. Stay current with advancements in generative AI, NLP, and prompt engineering techniques. Contribute to building internal documentation, style guides, and prompt libraries. --- Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, Data Science, Linguistics, or a related field (PhD a plus). 2+ years of experience working with LLMs, AI systems, or NLP frameworks. Strong understanding of transformer models, prompt engineering, and zero/few-shot learning. Must have experience with Prompt response and design Experience using OpenAI (ChatGPT, GPT API), Anthropic, Cohere, Hugging Face, or similar platforms. Proficiency in Python and use of AI libraries (LangChain, LlamaIndex, etc.). Excellent writing skills and a sensitivity to language nuance, tone, and context. Analytical thinker with a structured approach to testing and evaluation. ---

Role : Data Scientist Experience: 610 Years Salary : 35 L Upto Location : Bangalore Notice Period: 30 Days max ( Immediate Joiners Preferred ) Note : We are Open for both Contract or FTE Job Description: We are seeking a Data Scientist with strong experience in natural language processing and generative AI to build intelligent systems that extract information from PDFs, power chatbots, and implement retrieval-augmented generation (RAG) solutions. The ideal candidate should have a solid foundation in machine learning, experience working with unstructured text data. Key Responsibilities: Design and implement pipelines for extracting structured data from PDF documents using tools like PyMuPDF, PDFPlumber, or OCR libraries. Develop and fine-tune RAG pipelines combining vector databases (e.g., FAISS, Chroma) with LLMs for document-based question answering. Build and optimize conversational agents (chatbots) that use domain-specific data and generative AI models. Train and evaluate machine learning and NLP models for classification, entity extraction, summarization, etc. Collaborate with engineering and product teams to integrate AI capabilities into production systems. Monitor model performance and continually improve accuracy and relevance of generated responses. Requirements: Strong Python skills and experience with libraries like Hugging Face Transformers, LangChain, or LlamaIndex. Strong knowledge of ABC cloud tools (AWS or Azure) Familiarity with vector databases and embedding models (OpenAI, Cohere, SentenceTransformers). Experience with PDF data extraction techniques and tools. Solid understanding of supervised/unsupervised ML, deep learning, and NLP techniques. Experience working with LLMs and knowledge of prompt engineering and fine-tuning. Bachelors or Masters degree in Computer Science, Data Science, or a related field.

Role & responsibilities Key Responsibilities Architect and implement AI/ML/GenAI pipelines , automating end-to-end workflows from data ingestion to model deployment and monitoring. Develop scalable, production-grade APIs and services using FastAPI, Flask , or similar frameworks for AI/LLM model inference. Design and maintain containerized AI applications using Docker and Kubernetes . Operationalize Large Language Models (LLMs) and other GenAI models via cloud-native deployment (e.g., Azure ML, AWS Sagemaker, GCP Vertex AI). Manage and monitor model performance post-deployment, applying concepts of MLOps and LLMOps including model versioning, A/B testing, and drift detection. Build and maintain CI/CD pipelines for rapid and secure deployment of AI solutions using tools such as GitHub Actions, Azure DevOps, GitLab CI . Implement security, governance, and compliance standards in AI pipelines. Optimize model serving infrastructure for speed, scalability, and cost-efficiency. Collaborate with AI researchers to translate prototypes into robust production-ready solutions. Shift: 11am-8pm

Dear Aspirants, Urgent Hiring!!! Desired Candidate Profile 3+ years of experience Location: Bangalore-Electronicity Mandatory skills: Automation testing . . Exp : 3+ yrs (Only) You can register by sharing your CV, Notice period and Expected CTC to 9363648148 Whatsapp for immediate response (May not be available for call). Apply If you are ready to work from office Bangalore location . we are not considering candidates with less than 3 years of experience, Relocation candidates and notice period higher than 10 days. Proficiency in Python for AI/ML Development Strong command of Python and its ecosystem is essential for building and scaling AI applications. Experience with LLM Technologies and Architectures Includes API integrations (e.g., OpenAI, Anthropic), Retrieval Augmented Generation (RAG), vector databases, and embedding models. Backend Development and API Engineering Ability to develop and maintain backend services and APIs that support AI functionality. Relevant years of experience: 3+ years

Data Scientist with 5+ years of relevant experience in: Python, SQL, NLP, LLM, GenAI, H2O

Greetings from Futurea4! We are looking for a passionate and experienced Senior Data Scientist to drive innovation in the world of Gen AI, NLP, LLMs , and MLOps . Position : Senior Data Scientist Gen AI | NLP | LLM | MLOps Locations : Bangalore | Pune | Noida | Gurgaon | Hyderabad Experience : 6 to15 Years Joiners Preferred : Immediate or Short Notice Key Responsibilities Design and implement advanced NLP and Gen AI models using cutting-edge LLMs (e.g., GPT, LLaMA, Mistral). Fine-tune and customize LLMs through LoRA , PEFT , and prompt engineering techniques. Develop scalable ML pipelines and ensure smooth deployment via MLOps best practices. Translate business challenges into impactful AI-powered solutions . Monitor and improve model performance for accuracy and scalability. Create documentation and foster cross-functional knowledge sharing. Required Skills Strong hands-on experience in Generative AI , NLP , and LLM development (using frameworks like Hugging Face, spaCy, LangChain). Expert knowledge of Python , TensorFlow/PyTorch , and the ML lifecycle. Deep MLOps know-how: CI/CD, model monitoring, versioning, and deployment workflows. Cloud-native development experience (AWS, Azure, or GCP) and container tools ( Docker , Kubernetes ). Experience with large-scale data handling and data engineering principles. Nice to Have Familiarity with RAG pipelines , vector databases , and advanced prompt tuning. Exposure to multi-modal architectures , transformer models , and open-source LLMs . Publications or community involvement in AI research or development. Apply Today If you're eager to build the future of AI and ready to take on exciting challenges, we want to hear from you.

Role & responsibilities Design and implement LLM architectures (e.g., transformer variants) Pretrain and fine-tune models on large-scale datasets Apply techniques like LoRA, PEFT, DPO, or RLHF to improve model alignment Optimize training using frameworks. Evaluate models Collaborate with data and product teams to align model capabilities with use cases Key skills: Python, AI, LLM, Pytorch, SQL, NLP Preferred candidate profile Perks and benefits

Dear Candidates, Greetings!! We are hiring for one of the Globalized Motor Vehicle Manufacturing MNC. Job Type : FTE Job Role :- AI Engineer Experience: 4 to 5 Years Location : Bangalore Work Mode : Work From Office Notice Period : Serving to 30 days Budget : As Per Market Standards Mandatory Skills : AI Solution, Machine Learning, Data Forecasting, Pyspark, Data bricks, Linux, Azure, Experience in building agentic AI solutions, Familiarity in Python & Pandas. Interested candidates can share their updated resume on Gurpreet@selectiveglobalsearch.com

We are looking for a Generative AI Integration Developer to join our client's team and work on cutting-edge AI solutions. The ideal candidate should have hands-on experience with Large Language Models (LLMs) and Foundation Models, integrating them into enterprise applications. Job Title: Generative AI Integration Developer Experience: 7 12 years overall experience including a minimum 3+ years of hands-on experience in AI/ML development, LLM integration, or Generative AI agent development, with a strong focus on prompt engineering and fine-tuning pre-trained models Employment Type: Full-Time Salary: Best in the industry Key Responsibilities: Develop and integrate LLMs (e.g., OpenAI, Claude, Titan) using APIs. Design and build AI-powered interfaces and agents for seamless user interaction. Implement prompt engineering techniques to optimize AI responses. Work on Python-based microservices using Flask, Django, or similar frameworks. Collaborate with cross-functional teams to deploy AI solutions. Monitor and optimize AI performance using analytics tools. Stay updated with the latest trends in Generative AI and NLP. Required Skills: 712 years in software development with at least 3 years in AI/ML, LLM integration, or Generative AI agent development. Proven expertise in prompt engineering and fine-tuning pre-trained models for AI solution development. Hands-on experience integrating LLMs (e.g., OpenAI, Anthropic, Hugging Face) via APIs, with knowledge of model selection, optimization, and deployment. Ability to design AI agents/interfaces and implement RAG systems—especially in projects involving numeric data analysis and response generation. Strong grasp of NLP concepts and experience applying AI to structured/numeric data, including preprocessing, pattern detection, and summarization. Advanced skills in Python with frameworks like FastAPI, Flask, or Django, and experience in building AI microservices and consuming third-party APIs. Ability to design and implement microservices tailored for AI/LLM integration in scalable environments. Practical experience deploying AI on AWS using services like Amazon Bedrock, Lambda, S3, Step Functions, and DynamoDB. Familiarity with CI/CD pipelines, cloud-native deployments, infrastructure automation, and building AI chatbots on cloud platforms. Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related technical field. If you're passionate about AI and want to work on innovative solutions, apply now!

As a Technical Consultant at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise We are seeking a highly skilled and experienced IIoT (Industrial Internet of Things) Engineer with a strong focus on OPC UA (Unified Architecture) and companion specifications, as well as expertise in edge computing. The ideal candidate will play a crucial role in designing, implementing, and maintaining IIoT solutions that enhance the efficiency, reliability, and security of industrial operations Document solution architectures, design decisions, implementation details, and lessons learned. Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Preferred technical and professional experience Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus Demonstrate a growth mindset to understand clients' business processes and challenges

System Analsyt -Data Scientist lead Job Title: System Analyst Data Scientist Lead Location: Pune Kalyani Nagar Shift Timing: General Shift Experience: 7-15 years (Minimum 2 years in a leadership/management role) About Cybage: Cybage Software is a technology consulting organization and the head office is in Pune; you will get an opportunity to be a part of highly skilled talent pool of more than 7000 employees. We have our operations hub in GNR and Hyderabad as well and we have also marked our presence in USA, UK, Japan, Germany, Ireland, Canada, Australia, and Singapore. We provide seamless services and dependable deliveries to our clients from diverse industry verticals such as Media and Advertising, Travel and Hospitality, Digital Retail, Healthcare and Life Sciences, Supply chain and logistics, and Technology. Role Overview We are looking for a dynamic and experienced System Analyst Data Scientist Lead to join our growing AI & Data Science team. In this role, you will lead projects and collaborate with cross-functional teams to build and deploy cutting-edge machine learning solutions that drive business value. Skills required: Minimum 5+ years of experience in data science, with at least 2 years in a leadership or team management role. Proficiency in Natural Language Processing (NLP) techniques such as LDA, embeddings, Retrieval-Augmented Generation (RAG). Experience in time series forecasting, statistical modeling, and predictive analytics. Hands-on experience with Databricks, Azure ML stack, Python, and Django. Solid understanding of end-to-end data science workflows, from data engineering to model deployment. Ability to collaborate across diverse teams and communicate technical concepts clearly to stakeholders. Responsibilities: Build and deploy end-to-end ML pipelines, including data preprocessing, model training, and production deployment. Implement supervised, unsupervised, and deep learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Collaborate with data scientists and engineers to integrate ML models into production systems. Use MLOps tools like MLflow or Kubeflow for CI/CD and model lifecycle management. Monitor and optimize deployed models for performance and scalability. Stay updated on ML advancements and contribute to innovation within the team. Shift timings General shift Location Pune-Kalyani Nagar Its good to have: 60% & above in any two of the following and 55% & above in the third Secondary, Higher Secondary (or it s equivalent) and Graduation level (aggregate) Strong Communication & interpersonal Skills.

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. Qualifications2+ 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 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. Responsibilities Credit 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.

Role & responsibilities Breadth of knowledge in areas of computer vision including either classical methods or ML. These areas may include Image Enhancement, SLAM, calibration, scene understanding, gaze tracking, human representation, and activity recognition. Exposure to GenAI, object detection, facial recognition, content analysis, and behavior analysis models, Experience in implementing Multi Camera Unified Intelligence use cases. Experience leveraging LLMs and developing Agentic AI modules is a good to have Candidates should have exposure to modern innovative techniques including vision transformers, foundation models, and vision-language models, with a focus on integrating these methods into resource-constrained environments. Experience in reusable /libraries, and techniques (e.g., OpenCV, TensorFlow, PyTorch) for Video Analytics Experience in optimizing and fine-tuning ISP pipelines, including tasks like noise reduction, color correction, demosaicing, and dynamic range enhancement.

3 yrs dev exp with Python, Django, AWS, PostgreSQL. Strong in Java, familiar with Golang & frontend. Hands-on with LLMs & GenAI. Skilled in debugging, version control, and agile tools