525 Generative Ai Jobs

Senior Data Scientist Gen AI Experience: 3 - 6 Years Exp. Salary : INR 25-33 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 10:00AM to 7:00PM IST Opportunity Type: Onsite (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Gen AI Good to have skills : MDM platforms Blend360 (One of Uplers' Clients) is Looking for: Senior Data Scientist Gen AI who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description We are hiring a Senior Data Scientist (Generative AI) to spearhead the development of advanced AI-powered classification and matching systems on Databricks. You will contribute to flagship programs like the Diageo AI POC by building RAG pipelines, deploying agentic AI workflows, and scaling LLM-based solutions for high-precision entity matching and MDM modernization. Key Responsibilities Design and implement end-to-end AI pipelines for product classification, fuzzy matching, and deduplication using LLMs, RAG, and Databricks-native workflows. Develop scalable, reproducible AI solutions within Databricks notebooks and job clusters, leveraging Delta Lake, MLflow, and Unity Catalog. Engineer Retrieval-Augmented Generation (RAG) workflows using vector search and integrate with Python-based matching logic. Build agent-based automation pipelines (rule-driven + GenAI agents) for anomaly detection, compliance validation, and harmonization logic. Implement explainability, audit trails, and governance-first AI workflows aligned with enterprise-grade MDM needs. Collaborate with data engineers, BI teams, and product owners to integrate GenAI outputs into downstream systems. Contribute to modular system design and documentation for long-term scalability and maintainability. Qualifications Bachelors/Masters in Computer Science, Artificial Intelligence, or related field. 5+ years of overall Data Science experience with 2+ years in Generative AI / LLM-based applications. Deep experience with Databricks ecosystem: Delta Lake, MLflow, DBFS, Databricks Jobs & Workflows. Strong Python and PySpark skills with ability to build scalable data pipelines and AI workflows in Databricks. Experience with LLMs (e.g., OpenAI, LLaMA, Mistral) and frameworks like LangChain or LlamaIndex. Working knowledge of vector databases (e.g., FAISS, Chroma) and prompt engineering for classification/retrieval. Exposure to MDM platforms (e.g., Stibo STEP) and familiarity with data harmonization challenges. Experience with explainability frameworks (e.g., SHAP, LIME) and AI audit tooling. Preferred Skills Knowledge of agentic AI architectures and multi-agent orchestration. Familiarity with Azure Data Hub and enterprise data ingestion frameworks. Understanding of data governance, lineage, and regulatory compliance in AI systems. Interview Process Online Assessment Technical Screenings -2 Technical Interviews - 2 Project Review Client Interview How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. The company has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace. About Uplers: Uplers is the #1 hiring platform for SaaS companies, designed to help you hire top product and engineering talent quickly and efficiently. Our end-to-end AI-powered platform combines artificial intelligence with human expertise to connect you with the best engineering talent from India. With over 1M deeply vetted professionals, Uplers streamlines the hiring process, reducing lengthy screening times and ensuring you find the perfect fit. Companies like GitLab, Twilio, TripAdvisor, and AirBnB trust Uplers to scale their tech and digital teams effectively and cost-efficiently. Experience a simpler, faster, and more reliable hiring process with Uplers today.

Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. Experience with SQL, Excel, Tableau/ Power BI, PowerPoint Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) Experience applying various machine learning techniques and understanding the key parameters that affect their performance Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs Excellent verbal and written communication Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: Connect with internal / external POC to understand the business requirements Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis Create project plan and sprints for milestones / deliverables Spin VM, create and optimize clusters for Data Science workflows Create data pipelines to ingest data effectively Assure the quality of data with proactive checks and resolve the gaps Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms Research whether similar solutions have been already developed before building ML models Create optimized data models to query relevant data efficiently Run relevant ML / DL algorithms for business goal seek Optimize and validate these ML / DL models to scale Create light applications, simulators, and scenario builders to help business consume the end outputs Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively Integrate and operationalize the models in client ecosystem Document project artifacts and log failures and exceptions. Measure, articulate impact of DS projects on business metrics and finetune the workflow based on

1. 12+ years of IT experience, focused on Power Platform solution & architecture. 2. Expertise in Power Apps, Power Automate, Dataverse, and building custom connectors. 3. Strong experience in designing and delivering enterprise-level Power Platform solutions. 4. Knowledge of DevOps practices for Power Platform, including CI/CD pipelines and version control 5. In-depth knowledge of Azure services (Logic Apps, Azure Functions) and integration with Power Platform 6. Proven experience in defining and enforcing governance frameworks, security models, and best practices for Power Platform implementations. 7. Experience in architecting integrations between Power Platform and other business systems (e.g., Dynamics 365, Microsoft 365, external APIs) 8. Experience with Generative AI and AI-driven automation within Power Platform 9. Ability to collaborate with business stakeholders, developers, and cross-functional teams. 10. Excellent communication skills, capable of explaining complex technical solutions to non-technical stakeholders. 11. Strategic thinking and problem-solving capabilities for designing innovative solutions 12. Experience with Power Platform testing, quality assurance, and continuous improvement processes 13. Proficiency in Python for custom development and advanced automation (desirable) 14. Familiarity with ITIL, Agile, or other project delivery frameworks (desirable)

Key Responsibilities : 1. Einstein Analytics : Develop and maintain Einstein Analytics solutions, including data preparation, data modeling, and dashboard creation. 2. Einstein Prediction Builder : Develop and maintain predictive models using Einstein Prediction Builder, including data preparation, model training, and model deployment. 3. Einstein Discovery : Develop and maintain Einstein Discovery solutions, including data preparation, insight generation, and recommendation engines. 4. AI-Powered Solutions : Design and deploy AI-powered solutions using Salesforce Einstein, including chatbots, virtual assistants, and predictive maintenance. 5. Integration : Integrate Salesforce Einstein with other Salesforce products, including Sales Cloud, Marketing Cloud, and Service Cloud. 6. Data Preparation : Prepare and manage data for use in Einstein Analytics, Einstein Prediction Builder, and Einstein Discovery, including data cleansing, data transformation, and data loading. 7. Model Training and Deployment : Train and deploy machine learning models using Einstein Prediction Builder, including model selection, hyperparameter tuning, and model evaluation. 8. Solution Deployment : Deploy Einstein solutions to production environments, including configuration, testing, and validation. Requirements : 1. Salesforce Experience : At least 6 years of experience with Salesforce, including Sales Cloud, Marketing Cloud, and Service Cloud. 2. Agentforce Experience : At least 2 years of experience with Salesforce Agentforce, including Einstein Analytics, Einstein Prediction Builder, and Einstein Discovery. 3. AI and Machine Learning Experience : At least 2 years of experience with AI and machine learning, including machine learning frameworks, deep learning, and natural language processing. 4. Programming Skills : Strong proficiency in programming languages, such as Python, Java, and Apex. 5. Data Analysis and Visualization : Strong skills in data analysis and visualization, including data preparation, data modeling, and data visualization. 6. Communication and Collaboration : Excellent communication and collaboration skills, including the ability to work with cross-functional teams and stakeholders.

Junior GenAI Engineer Join CodeFires core GenAI team and turn the latest research into real-world products. What Youll Tackle Prototype with LLMs: Evaluate multiple models, fine-tune, and embed them in live apps. Prompt Engineering: Craft, test, and measure prompts for accuracy, speed, and cost. Rapid Research Production: Scan new papers/tools weekly and turn the best ideas into POCs. Shape the Practice: Be part of the think-tank defining CodeFires GenAI roadmap. What Makes You a Fit Recent grad (any branch) from IIT/NIT/IIIT or any reputed institute +a proven passionate coder with standout AI projects. Solid Python plus experience with PyTorch/TensorFlow and/or LangChain, OpenAI, etc. Sharp analytical mind, research curiosity, and a bias for shipping. GitHub, papers, hackathon wins, or side projects that scream I live GenAI. Why CodeFire Immediate impact: Your code lands in production, not in a drawer. Mentorship: Work directly with our CEO & IIT alumni tech leads. Culture of builders: Flexible hours, rapid iterations, zero red tape. Full-stack exposure: From model selection to UX, see the whole product life-cycle. Apply Now Watch this short message from our CEO Pranjal Srivastava and answer accordingly. Check why and who should apply https://www.youtube.com/watch?v=V5Z1DHvhup0&feature=youtu.be Email your rsum plus links to your best AI work to hr@codefire.in or WhatsApp +9170422 03446 . Build the future with usone prompt at a time.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Job description Role & responsibilities We are seeking a skilled AI/ML Engineer proficient in Python to join our dynamic team. In this role, you will collaborate with cross-functional teams to design, develop, and deploy machine learning models and AI systems. You will be responsible for implementing algorithms and workflows that enable our organization to leverage data for insightful decision-making and innovative product solutions. Key Responsibilities:- Develop machine learning models and algorithms using Python and relevant libraries (e.g., Tensor Flow, PyTorch, sci-kit-learn). Min 6 months of experience in Gen AI and Proficiency in could technologies such as AWS, GCP or azure. Collaborate with data engineers to design and implement data pipelines for efficient data processing, analysis, and model training. Apply machine learning techniques to solve complex business problems and optimize existing processes. Evaluate and benchmark different machine learning models to determine optimal solutions. Work closely with product managers and stakeholders to understand business requirements and translate them into technical solutions. • Implement scalable and reliable machine learning infrastructure and productionize models. Stay updated with the latest developments in AI/ML research and apply them to improve our systems continuously. Participate in code reviews, knowledge sharing, and contribute to the overall growth of the AI/ML team. Work from office Afternoon shift NO ONLINE INTERVIEW : Role: Data ScientistIndustry Type: IT Services & ConsultingDepartment: Data Science & AnalyticsEmployment Type: Full Time, PermanentRole Category: Data Science & Machine Learning EducationUG: Any GraduateKe

We are organizing a Virtual Hiring Drive on Saturday, 28th June 2025 across all Kanini locations Chennai, Coimbatore, Bangalore, and Pune Job Description: We are looking for an experienced and passionate Data Scientist with a strong background in Python programming and Azure services. The ideal candidate will have hands-on expertise in deploying GenAI/OpenAI-based solutions , working with FastAPI , vector databases , and RAG (Retrieval-Augmented Generation) architectures. Experience in CI/CD , NLP , computer vision (CV) , and deep learning is essential. Key Responsibilities: Design, develop, and deploy machine learning and GenAI solutions. Build and optimize RAG-based architectures using vector DBs, embeddings, and chunking techniques. Develop RESTful APIs using FastAPI and Django. Work with Azure services including Form Recognizer , Azure ML , and Data Storage . Integrate CI/CD pipelines for scalable deployment. Collaborate with cross-functional teams (Product, Engineering, DevOps). Handle structured and unstructured data from various sources including NoSQL databases. Implement NLP and Computer Vision solutions using pre-trained and custom models. Optimize performance and cost of deployed models in production. Primary Skills Proficient in Python programming with strong experience in FastAPI and Django frameworks Hands-on expertise with Microsoft Azure services , including Form Recognizer and Azure Machine Learning Experience in Generative AI , OpenAI APIs , and Large Language Models (LLMs) Skilled in building Retrieval-Augmented Generation (RAG) solutions Familiar with Vector Databases such as FAISS , ChromaDB , Pinecone , and Milvus Knowledge of embedding generation and text chunking techniques Experience in Natural Language Processing (NLP) and Computer Vision (CV) Strong understanding of Machine Learning and Deep Learning techniques Proficient in CI/CD pipeline tools like Jenkins and GitHub Actions Experience working with NoSQL databases , including MongoDB and Cassandra Location: Chennai, Coimbatore, Bangalore, Pune

Your tasks As a team member of the Group Sector Central Function Technology of ContiTech, you will be globally responsible to drive success of applied data science and effective usage in all areas of the organization. Design and implement innovative data-drive solutions to solve complex business problems, using cutting-edge techniques to build up customer centric platforms to reduce complexity, ensure standards, maximize cost savings as well as developing innovative material-driven solutions for a carbon-neutral and 100% circular product portfolio. You Consult on effectively applying Data Science methodology, technology, and good practices, complementing AI/DS platform owners, AI/DS sector owners, AI/DS project owners. Collaborates with stakeholders to identify data and AI opportunities, translates business needs into actionable data requirements and success metrics, and drives prioritization of use cases based on feasibility and impact . Develop best practices, guidelines, and standards for data science in collaboration with AI/DS stakeholders to build solutions. Maintain a deep understanding of the business and industry to identify emerging trends and research to actively drive technology opportunities. Work closely with cross-functional teams to identify opportunities for improving business performance and delivering impactful results. Develop and implement models and algorithms using machine learning, deep learning, natural language processing, and statistical analysis. Lead the development and implementation of data pipelines and infrastructure to support data analysis and modeling. Establish and maintain partnerships with internal and external partners. Optimize data-driven decision-making processes to enhance operational efficiency and effectiveness. Ensure data quality and integrity through rigorous validation and testing procedures. Your Qualifications University degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. Extensive knowledge of data science techniques including descriptive and inferential statistics, big data and data mining technologies, and machine learning. Extensive experience in Data Science, AI, and Machine Learning, with a solid understanding of algorithms, predictive models, deep learning, and natural language processing (NLP). Strong technical proficiency in programming languages and tools (Python, R, TensorFlow, PyTorch, etc.) More than 5 years of dedicated experience in various data science-related roles in the industry. Excellent communication and leadership skills. Critical thinking, organizational skills, and a problem-solving mindset. Experience in a manufacturing industry is a plus. Inspire your stakeholders and contact partners with effective communication and high intercultural sensitivity. Collaborative, team player attitude and convinced that networking and knowledge sharing are key drivers for success. Up-to-date on the latest trends in the industry concerning classical data science, data mining, advanced analytics, etc. Proven ability to translate complex data into actionable insights for non-technical stakeholders. Demonstrated ability to work in a fast-paced, dynamic environment and adapt to changing priorities.

We are seeking a highly skilled and innovative Data Scientist with a strong focus on Generative AI, NLP, and Large Language Models (LLMs). The ideal candidate will design, develop, and deploy end-to-end data science solutions that harness the power of advanced ML, deep learning, and Gen AI technologies to drive real-world impact. Key Responsibilities: Design and implement scalable data science solutions using Generative AI, NLP, and ML techniques. Develop, fine-tune, and evaluate Large Language Models (LLMs) such as GPT, BERT, and similar architectures. Analyze structured and unstructured data to generate actionable insights for business problems. Collaborate cross-functionally with engineering, product, and business teams to integrate AI models into production systems. Conduct cutting-edge research in Gen AI and deep learning; evaluate and apply recent advancements. Build and maintain robust pipelines for model training, evaluation, monitoring, and deployment. Communicate complex technical findings clearly to technical and non-technical stakeholders. Required Skills & Qualifications: Strong hands-on experience with Generative AI, LLMs (e.g., OpenAI, Hugging Face Transformers, etc.). Proven expertise in core NLP tasks: text classification, summarization, named entity recognition, sentiment analysis, etc. Proficient in Python and related libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch. Experience developing, validating, and deploying ML models in production environments. Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings, and semantic search. Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps tools/workflows (CI/CD, model monitoring, etc.). Preferred Qualifications: Experience in prompt engineering, Retrieval-Augmented Generation (RAG), or fine-tuning/customizing LLMs. Contributions to AI research papers, open-source projects, or participation in ML competitions (e.g., Kaggle) is a plus. Knowledge of responsible AI practices, model interpretability, and bias mitigation techniques.

AI Engineer JD (2+ years) Job Description Were searching for a hands-on AI engineer who can take modern LLMs from prototype to production, orchestrating multi-agent workflows using libraries such as LlamaIndex Workflows, LangGraph , and structured function calling . You should bring a solid foundation in classical ML (e.g., XGBoost) and deep learning with transformer-based models especially LLaMA and Qwen-family models along with experience in Retrieval-Augmented Generation (RAG) pipelines. A track record of building reliable, scalable systems is essential. Responsibilities: Design, build, and deploy ML/DL models for vision (YOLO), tabular (XGBoost),, and NLP / GenAI use-cases (function calling, RAG). Work on fine-tuning and deploying LLMs using platforms like Hugging Face and PyTorch. Engineer agent-based LLM solutions Compose multi-step, tool-calling workflows with LlamaIndex or LangGraph. Implement structured function calling and dynamic tool selection for Retrieval-Augmented Generation (RAG) pipelines. Orchestrate agent state, memory, and conversation context to solve complex user tasks. Fine-tune and serve LLMs on Hugging Face / PyTorch, including efficient-tuning methods (LoRA, QLoRA, PEFT). Operate on cloud (Azure preferred, AWS acceptable) set up training jobs, GPU/ACI deployments, CI/CD, observability, and cost governance. Collaborate cross-functionally with product, data, and frontend teams to turn fuzzy ideas into measurable impact. Build FastAPI micro-services for low-latency inference, streaming responses, and secure integration with downstream systems. Requirements: Proficiency in Python, with exposure to FastAPI and/or Java. Solid understanding and practical experience in Machine Learning with models like XGBoost. Experience with Deep Learning using YOLO, OCR frameworks, and PyTorch. NLP / GenAI: LLM fine-tuning, prompt engineering, RAG design. Hugging Face Transformers, PEFT, vector databases. Experience implementing agent frameworks (LlamaIndex, LangGraph, LangChain Agents) and function-calling patterns. MLOps: Docker, CI/CD, experiment tracking, model versioning, monitoring, and rollback strategies. Cloud: Azure ML / Azure Functions / AKS (preferred) or AWS SageMaker / Lambda basics. Bonus: experience with Triton / vLLM, streaming websockets, or GPU cost-optimization. Benefits of Working with Us: Best of Both Worlds: Enjoy the enthusiasm and learning curve of a startup combined with the deliveries and performance of an enterprise service provider. Flexible Working Hours: We offer a delivery-oriented approach with flexible working hours to help you maintain a healthy work-life balance. Limitless Growth Opportunities: The sky is not the limit when it comes to learning, growth, and sharing ideas. We encourage continuous learning and personal development. Flat Organizational Structure: We don't follow the typical corporate hierarchy ladder, fostering an open and collaborative work environment where everyone's voice is heard. As part of our dedication to an inclusive and diverse workforce, TechChefz Digital is committed to Equal Employment Opportunity without regard to race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. If you need assistance, you may contact us at joinus@techchefz.com

Location: Remote Timings: Full Time (As per company timings) Notice Period: (Immediate Joiner - Only) Experience: 4 Years Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

JD: Overall 5+ years of experience in IT Industry Good Exposure in Python, Gen AI. Interested share your CV to preetha.p@tekskills.in Thanks & Regards, Preetha Parthiban IT Recruiter India Recruitment preetha.p@tekskills.in | P: +91 40 67 28 49 29 YOUR IT CONDUIT INDIA | USA | CANADA | UK I AUSTRALIA www.tekskillsinc.com | Follow us on LinkedIn ISO 9001:2015 | Appraised at CMM Level 3 | WMBE Certified Company

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Job Title: Senior MLOps Engineer Location : Pan India (WFO) Experience Range: 8-12 years Primary Key skills: MLOps Key Responsibilities: Design, develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, maintenance, and scalability. Automate the retraining, testing, and validation processes for ML models. Collaborate with cross-functional teams, including data science, software engineering and DevOps, to integrate ML models into production systems. Monitor model performance, diagnose issues, and implement improvements. Ensure scalability, reliability, and compliance of ML systems in production. Optimize infrastructure costs while maintaining high system performance. Stay up-to-date with the latest developments in MLOps, machine learning and AI, and apply new techniques to improve existing models and processes. Qualifications: Education: Bachelors or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field. Experience: Solid experience as a MLOps Engineer, Machine Learning Engineer, DevOps Engineer, or similar role. Experience in the retail industry or e-commerce is highly desirable. Technical Skills: Strong experience with Infrastructure as Code frameworks and languages (Terraform, Bicep or ARM) Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, etc.). Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes). Proficiency in CI/CD tools and cloud platforms (AWS, Azure, or Google Cloud). Knowledge of model monitoring and evaluation metrics. Familiarity with version control systems, such as Git, and model versioning tools like MLflow or DVC. Experience with Generative AI product deployment is desirable. Experience with big data using Databricks, Snowflake, Apache Spark or Hadoop is desirable. – some of these System level architecture understanding including scaling, MLOps, model/data monitoring, andensuring a deterministic pipeline. Soft Skills: Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. A proactive attitude and a passion for continuous learning and innovation. Role & responsibilities Preferred candidate profile

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

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

Navigate the development journey for PARIS 2.0 delivering seamless and scalable software solutions across web and mobile, ensuring a smooth voyage for all users Driving engineering best practices and architecting robust, maintainable, and high-performance systems that guideteams through complexity to user-centric solutions Translate user requirements into cutting-edge software, building applications that feel less like tools and more like second nature for maritime professionals Champion the agile voyage, embedding best engineering practices and a culture of continuous improvement into Fleet's DNAturning What if into What's next Technical Leadership & Data-Driven Development Lead deep-dive technical explorations, identifying performance bottlenecks, security vulnerabilities, and architectural improvements to ensure a future-ready tech stack. Using data to leverage monitoring tools, analytics and industry trends to validate decisions and measure impact. Develop technical roadmaps, API blueprints, and integration strategiesto ensure our platforms are scalable, resilient, and adaptable to future maritime challenges Enforce best practices in testing, CI/CD, and DevOps to keep our software fleet sailing smoothly Craft the Compass: Software Execution & Quality Manage the full software development lifecyclefrom design and architecture to coding, testing, and deploymentensuring every feature is fit for purpose and aligns with Fleet's mission Maintain a North Star of engineering excellence, upholding rigorous coding standards and fostering a culture of clean, maintainable, and efficient code Balance speed and precision, implementing agile workflows that harness insights while ensuring software is both innovative and robust Captain the Crew: Leadership, People Management & Cross-Functional Master Mentor and lead a crew of engineers, shaping them into people who champion best practices in software development and system architecture Foster a high-performing team, creating an environment where engineers feel empowered, motivated, and aligned with the company's mission Provide continuous feedback and career guidance, conducting regular 1:1s, performance reviews, and coaching sessions to help team members grow and excel Resolve bottlenecks and team challenges, ensuring smooth collaboration between engineering, product, design, and business teams. Collaborate closely with designers, product managers, and business leaders, ensuring engineering is a trusted co-captain in Fleet's innovation journey. Job Experience, Functional Knowledge and QualificationsIndicate the minimum and preferred education and experience for this job and any licenses and certifications required. 1.3+ years of experience of leading software engineers in an agile environment using either SCRUM, XP or Kanban Hands-on experience in a Software Engineering role working with JavaScript, Node and/or Java Track record of delivering complex solutions, as part of a high-performing team, in challenging circumstances Experience with Generative AI (GenAI) technologies and their use in software development Effective communication skills, verbally and in writing both with onshore and remote team members Ability to think strategically and make data-driven decisions while working under pressure

Notice Period: Maximum 30 days Location: Bangalore, Chennai, Kolkata, Pune, and Hyderabad Note: Candidates based in Hyderabad must attend in-person interviews for the second round. Role Summary: Generative AI Specialist Mandatory Skills: Gen AI, LLMs, ML/DL/NLP, RAG, LangChain, Mistral, LLaMA, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DBs Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (e.g., Kubeflow, MLflow), Kubernetes, GitHub/Bitbucket, Azure DevOps, GPT-4 Responsibilities: Design, develop, and deploy generative AI solutions using modern ML/DL techniques. Work with large-scale datasets; handle preprocessing and model optimization. Build applications using LLMs and frameworks like LangChain, leveraging models like Mistral, LLaMA, GPT-4. Research and implement cutting-edge GenAI algorithms and architectures. Ensure Responsible AI compliance and monitor model performance post-deployment. Collaborate with cross-functional teams for solution integration and data engineering. Drive innovation by staying up to date with AI trends. Provide technical leadership, mentorship, and contribute to project governance and stakeholder communication. If you meet the requirements and are looking for a new opportunity, we'd love to hear from you! Interested candidates can send their resumes to admin@spearheadps.com OR Contact us via call/WhatsApp at 9899080360

We are currently seeking a Project Manager Contact Center for one of our banking clients. Work location: India ( Bangalore, Pune, Hyderabad) Work setting: remote We are looking for a strategic and technically adept Channels Project Manager to lead initiatives within our Digital Banking Transformation program. The role is responsible for delivering Contact Center Automation, AI/ML-driven customer engagement solutions, and digital self-service channels aligned with regulatory requirements and customer experience standards in the banking sector. Key Responsibilities: Lead the end-to-end delivery of digital customer interaction projects across voice, chat, mobile, and online banking platforms. Implement AI/ML-enabled contact center solutions, including virtual assistants, conversational IVRs, and intelligent routing to enhance efficiency and reduce operational cost. Drive digital transformation of contact centers, with a focus on improving First Contact Resolution (FCR), Net Promoter Score (NPS), and cost-to-serve. Collaborate closely with Compliance, Risk, IT Security, and Data Governance teams to ensure all solutions meet regulatory and data protection requirements (e.g., RBI, GDPR, etc.). Manage third-party vendors, fintech partnerships, and platform integrators to ensure timely and quality delivery. Integrate Core Banking Systems (CBS), CRM, and ticketing platforms for unified customer views. Use analytics to track usage, efficiency gains, and customer satisfaction across automated and digital channels. Required Qualifications: Bachelor's degree in Information Technology, Engineering, Business Administration, or related field; MBA or Masters in Digital Transformation or Banking Technology preferred. 510 years of experience in project/program management, with at least 3 years in banking or financial services. Strong background in contact center technologies (Genesys, NICE, Avaya, Cisco, etc.) and AI/ML automation tools. Demonstrated experience in digitizing customer service journeys in a regulated financial environment. Proficiency in Agile/Waterfall project delivery methods, and experience using Jira, MS Project, or similar tools.

Work Location: Chennai/ Bangalore Shift: General Shift Mandatory Skills: Gen AI, LLM, RAG, Lang chain, Llama, AI/ML, Deep Learning, Python, Tensorflow, Pytorch, Pandas, Prompt Engineering, Vector DB, MLOps Preferred Skills: AWS or GCP or Azure Cloud, GPT-4, SQL, Fast API/ API Development, Docker/ Kubernetes, Hadoop, Spark or Apache Flink Data Pipeline, Banking exposure. Job Description / Roles & Responsibilities (in Detail) : Educational Background: Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Programming Languages: Proficiency in Python, R, API development - Python/Fast API. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras etc. Gen AI & RAG: Experinced in GEN AI Models, Langchain/Langflow and Prompt Engineering Machine Learning: Strong understanding of machine learning algorithms, Deep Learning / Neural networks & Transfer Learning, Data Science: Experience with data analysis, data visualization, and statistical modeling. Big Data Technologies: Familiarity with big data processing frameworks like Hadoop, Spark, or Apache Flink or similar Data pipelines. Cloud Platforms: Experience with cloud services such as AWS, Google Cloud, or Azure for deploying AI solutions if good to have. Awareness on applied statistics, Experinced in Algorithms, Model development / evaluation and Data Preprocessing Exposure to ML Ops & Awareness of Containerisation with Docker/ Kubernetes Problem-Solving: Strong analytical and problem-solving skills with the ability to think critically and creatively. Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Team Collaboration: Ability to work effectively in a collaborative team environment and contribute to team success.

We are seeking a skilled and motivated individual to join our team. The ideal candidate will have experience working with Microsoft CoPilot Studio and Azure Communication Framework, with a passion for building scalable and reliable solutions. Key Responsibilities Design, develop, and implement custom applications using CoPilot Studio, ensuring alignment with business requirements. Integrate and maintain communication tools and services utilizing the Azure Communication Framework. Collaborate with product owners and technical leads to design effective workflows and solutions. Develop, test, and deploy end-to-end solutions, ensuring scalability, reliability, and maintainability. Troubleshoot, debug, and optimize applications for maximum performance and functionality. Conduct code reviews and follow best practices for code quality, version control, and testing. Stay updated with the latest trends and developments in Microsoft CoPilot, Azure technologies, and other relevant tools to enhance solutions.