14 Llm Architectures Jobs

The ideal candidate for the position should have a Master's degree in Computer Science, Data Science, or a related field, with a preference for a Ph.D. They should have 8-12 years of experience in a Data Scientist or equivalent role, including at least 4 years of specialized experience in Generative AI. This experience should involve leading technical development, mentoring teams, and troubleshooting and debugging GenAI models in production. Additionally, candidates should have experience working with financial data, applying NLP techniques, developing and testing Python code for GenAI solutions, integrating with vector databases, and monitoring MLOps pipelines. It is essential for the candidate to stay up-to-date with the rapidly evolving GenAI landscape, continuously learn new tools and techniques, and communicate technical concepts clearly to non-technical stakeholders. Candidates must possess demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation, including deploying, monitoring, and maintaining models in a live environment. Proof-of-concept work alone is not sufficient. Candidates should have expertise in various technical areas such as data structures, algorithms, object-oriented programming, scientific computing (NumPy, Pandas, SciPy), machine learning (Scikit-learn, XGBoost, LightGBM), deep learning (TensorFlow, PyTorch), and GenAI (Transformers, LangChain). Specific skills in LLM architectures, RAG, Advanced Chatbot Architectures, Prompt Engineering, Fine-tuning LLMs, and API Development are required. Expert-level Python skills are mandatory, including proficiency in core Python and key libraries for AI/ML and GenAI applications. The candidate should have proven abilities in designing, developing, and deploying complex GenAI projects, a deep understanding of LLMs, RAG, and advanced chatbot architectures, and experience in designing scalable API architectures for GenAI applications. Preferred qualifications include experience with MLOps, cloud computing platforms, conversational AI solutions, research contributions in Generative AI, and building and managing large datasets for training GenAI models. Strong technical leadership, mentorship skills, and excellent communication and collaboration skills are also essential for this role. Overall, the candidate should be able to articulate the challenges and successes of deploying GenAI solutions at scale, effectively convey technical concepts to diverse audiences, and work collaboratively with stakeholders to meet their needs.,

ABOUT XENONSTACK XenonStack is the fastest-growing data and AI foundry for agentic systems, enabling people and organizations to gain real-time and intelligent business insights. The company offers Agentic Systems for AI Agents through akira.ai, Vision AI Platform through xenonstack.ai, and Inference AI Infrastructure for Agentic Systems via nexastack.ai. THE OPPORTUNITY We are looking for a Forward Deployed Solutions Engineer Agentic Systems to partner closely with enterprise customers, understanding their business goals and designing tailored AI agent solutions that drive measurable outcomes. This role blends technical architecture, solution design, and on-the-ground enablement, ensuring successful deployment, adoption, and integration of XenonStack's Agentic AI platforms into complex enterprise environments. If you enjoy working directly with customers, solving high-impact problems, and shaping AI-powered transformation strategies, this role is for you. RESPONSIBILITIES Discovery & Solution Design: - Engage with client stakeholders to understand business workflows, challenges, and success metrics. - Design end-to-end AI agent solutions leveraging our Agentic Systems platforms. Technical Implementation Leadership: - Oversee integration of multi-agent orchestration, RAG pipelines, and context management into client environments. - Guide client engineering teams through deployment best practices. Configuration & Customization: - Develop tailored prompt templates, context flows, and tool integrations aligned with enterprise requirements. Enablement & Training: - Deliver workshops and hands-on sessions to upskill client teams in AgentOps, observability, and AI governance practices. Performance & ROI Tracking: - Establish metrics dashboards to track adoption, performance, cost efficiency, and business impact. Customer Advocacy: - Act as the voice of the customer to internal engineering and product teams, highlighting feature requests, workflow gaps, and optimization opportunities. Risk & Compliance Alignment: - Ensure deployed solutions meet enterprise security, compliance, and regulatory standards. SKILLS & QUALIFICATIONS Must-Have: - 4-6 years in solutions engineering, enterprise software delivery, or AI/ML consulting. - Strong technical understanding of LLM architectures, prompt engineering, and context pipelines. - Experience integrating agentic AI frameworks (LangChain, LangGraph, AgentBridge) into enterprise systems. - Familiarity with RAG, vector databases, and API/tool integration patterns. - Excellent client-facing communication and solution storytelling skills. - Ability to translate complex technical concepts into business-relevant outcomes. Good-to-Have: - Exposure to BFSI, GRC, SOC, or FinOps domains. - Familiarity with AI observability stacks and evaluation tools (Prometheus, OpenTelemetry, TruLens, Ragas). - Experience with compliance-driven deployments (GDPR, PCI-DSS, HIPAA). - Background in AI strategy consulting or transformation programs. CAREER GROWTH & BENEFITS Continuous Learning & Growth: - Certification sponsorships in AI solution architecture, multi-agent orchestration, and Responsible AI. - Hands-on exposure to enterprise AI transformations at scale. Recognition & Rewards: - Incentives for measurable customer impact and solution innovation. - Fast-track opportunities into AI Solutions Architecture Leadership roles. Work Benefits & Well-Being: - Comprehensive medical insurance and project-based allowances. - Cab facilities for women employees and special project perks. XENONSTACK CULTURE JOIN US & MAKE AN IMPACT! We foster a culture of cultivation with bold, human-centric leadership principles. We value deep work, experimentation, and ownership in every initiative, and we are on a mission to reshape how enterprises adopt AI + Human Intelligence systems. Product Values: - Obsessed with Adoption: Making AI accessible and enterprise-ready. - Obsessed with Simplicity: Turning complexity into seamless, intuitive AI experiences. Be a part of our vision to accelerate the world's transition to AI + Human Intelligence.,

We empower our people to stay resilient and relevant in a constantly changing world. We are looking for individuals who are always seeking creative ways to grow and learn, individuals who aspire to make a real impact, both now and in the future. If this resonates with you, then you would be a valuable addition to our dynamic international team. As a Graduate Trainee Engineer, you will have the opportunity to contribute significantly by: - Designing, developing, and optimizing NLP-driven AI solutions using cutting-edge models and techniques such as NER, embeddings, and summarization. - Building and operationalizing RAG pipelines and agentic workflows to facilitate intelligent, context-aware applications. - Fine-tuning, prompt-engineering, and deploying LLMs (such as OpenAI, Anthropic, Falcon, LLaMA, etc.) for specific domain use cases. - Collaborating with data scientists, backend developers, and cloud architects to construct scalable AI-first systems. - Evaluating and integrating third-party models/APIs and open-source libraries for generative use cases. - Continuously monitoring and enhancing model performance, latency, and accuracy in production environments. - Implementing observability, performance monitoring, and explainability features in deployed models. - Ensuring that solutions meet enterprise-level criteria for reliability, traceability, and maintainability. To excel in this role, you should possess: - A Master's or Bachelor's degree in Computer Science, Machine Learning, AI, or a related field. - Exposure to AI/ML, with expertise in NLP and Generative AI. - A solid understanding of LLM architectures, fine-tuning methods (such as LoRA, PEFT), embeddings, and vector search. - Previous experience in designing and deploying RAG pipelines and collaborating with multi-step agent architectures. - Proficiency in Python and frameworks like Lang Chain, Transformers (Hugging Face), Llama Index, Smol Agents, etc. - Familiarity with ML observability and explainability tools (e.g., Tru Era, Arize, Why Labs). - Knowledge of cloud-based ML services like AWS Sagemaker, AWS Bedrock, Azure OpenAI Service, Azure ML Studio, and Azure AI Foundry. - Hands-on experience in integrating LLM-based agents in production settings. - An understanding of real-time NLP challenges (streaming, latency optimization, multi-turn dialogues). - Familiarity with Lang Graph, function calling, and tools for orchestration in agent-based systems. - Exposure to infrastructure-as-code (Terraform/CDK) and DevOps for AI pipelines. - Domain knowledge in Electrification, Energy, or Industrial AI would be advantageous. Join us in Bangalore and be part of a team that is shaping the future of entire cities, countries, and beyond. At Siemens, we are a diverse community of over 312,000 minds working together to build a better tomorrow. We value equality and encourage applications from individuals who reflect the diversity of the communities we serve. Our employment decisions are based on qualifications, merit, and business requirements. Bring your curiosity and creativity to Siemens and be a part of shaping tomorrow with us. Explore more about Siemens careers at www.siemens.com/careers and discover the digital world of Siemens at www.siemens.com/careers/digitalminds.,

ABOUT XENONSTACK XenonStack is the fastest-growing data and AI foundry for agentic systems, enabling people and organizations to gain real-time and intelligent business insights. Agentic Systems for AI Agents: akira.ai Vision AI Platform: xenonstack.ai Inference AI Infrastructure for Agentic Systems: nexastack.ai THE OPPORTUNITY We are seeking an Agentic Infrastructure Observability Engineer to design, implement, and maintain visibility, monitoring, and assurance systems for large-scale AI agent deployments. This role focuses on observability, telemetry, and evaluation pipelines across multi-agent and multi-context workflows, ensuring AI systems are measurable, trustworthy, and compliant in enterprise and regulated environments. If you're passionate about SRE principles for AI, LLM evaluation, and agentic system transparency, this role offers the chance to shape observability for the next generation of intelligent automation. RESPONSIBILITIES Design and Implement Telemetry Pipelines Build observability infrastructure to capture logs, metrics, traces, and behavioral data from AI agents, orchestration layers, and integrated tools. Develop Evaluation Dashboards & KPIs Track accuracy, latency, reliability, cost, token usage, and success rates for agentic workflows. Enable Full-Stack Tracing Build execution flow tracing for multi-agent, multi-tool pipelines, with attribution for each decision, prompt, and retrieval step. Monitor Behavioral Reliability Detect and flag hallucinations, decision drift, prompt degradation, or tool misuse in real time. Integrate with Evaluation Frameworks Work with LLM eval tools like TruLens, Ragas, Arize AI, and custom scoring systems for continuous quality monitoring. Ensure Compliance & Auditability Implement observability features for regulatory audits (e.g., PCI-DSS, GDPR), including secure logging of prompts, retrieved context, and decisions. Cost & Resource Observability Track model/API usage, compute cost, and token consumption to enable optimization decisions. Collaborate Across Teams Partner with AgentOps Engineers, AI Interaction Engineers, and Model Reliability teams to turn observability insights into operational improvements. SKILLS & QUALIFICATIONS Must-Have: 35 years in SRE, DevOps, AI infrastructure, or ML systems engineering. Proficiency in Python and observability stacks (Prometheus, OpenTelemetry, Grafana, ELK, etc.). Familiarity with LLM architectures, multi-agent orchestration frameworks (LangGraph, LangChain, AgentBridge), and context pipelines. Experience with logging, tracing, and performance profiling for distributed systems. Understanding of LLM evaluation metrics (factuality, coherence, toxicity, cost efficiency). Knowledge of privacy and compliance standards for AI systems. Good-to-Have: Hands-on experience with LLM eval tools (TruLens, Ragas, Arize AI, Weights & Biases). Familiarity with RAG, vector databases, and knowledge graph-based retrieval. Experience in regulated industries (BFSI, healthcare, GRC). Background in anomaly detection or behavioral monitoring for ML systems. CAREER GROWTH & BENEFITS Continuous Learning & Growth Training and certifications in AI observability, LLM evaluation, and Responsible AI. Hands-on exposure to enterprise-scale agentic infrastructure. Recognition & Rewards Incentives for innovations in AI observability and monitoring. Fast-track opportunities into AI Reliability Architecture or Model Ops Leadership roles. Work Benefits & Well-Being Comprehensive medical insurance and project-based allowances. Cab facilities for women employees and special project perks. XENONSTACK CULTURE JOIN US & MAKE AN IMPACT! We foster a culture of cultivation with bold, human-centric leadership principles. We value deep work, experimentation, and ownership in every initiative, and we are on a mission to reshape how enterprises adopt AI + Human Intelligence systems. Product Values: Obsessed with Adoption Making AI accessible and enterprise-ready. Obsessed with Simplicity Turning complexity into seamless, intuitive AI experiences. Be a part of our vision to accelerate the world's transition to AI + Human Intelligence.,

As a Machine Learning Engineer (MLE) at Capco in Pune, with over 8 years of experience, you will be working in an inclusive environment that values diversity and individuality. Capco is a global technology and business consultancy specializing in the financial services sector, dedicated to helping clients succeed in an ever-evolving industry. Your key responsibilities will include having a strong understanding of LLM architectures, fine-tuning pre-trained models on domain-specific data, and working with concepts such as RAG, Prompt Engineering, and Vector DBs. You should also possess expertise in containerization and orchestration technologies like Kubernetes and Docker, along with in-depth knowledge of machine learning, deep learning, and NLP. Additionally, you will be managing prioritization and technology work for building NLP, ML & AI solutions, experimenting with LLM, and ensuring best practices for ML models integration and deployment. To excel in this role, you should have at least 8-10 years of experience in deploying end-to-end data science solutions, a strong technical background from a top-tier institute, and proficiency in training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformer. Skills in Python, SQL, Pandas, Pyspark, GitHub, Confluence, JIRA, and cloud platforms like Azure or GCP are essential. Moreover, experience in stakeholder management, communication, and presentation skills are required to effectively present technical solutions and features in business terms. At Capco, you will have the opportunity to work on projects that will revolutionize the financial services industry, along with a work culture focused on innovation, ongoing learning opportunities, a flat non-hierarchical structure, and competitive family-friendly benefits. If you are excited about advancing your career with Capco, we encourage you to apply and join us in creating lasting value for clients and employees. For more information about Capco and its people, please visit www.capco.com.,

As an AI Development and Integration specialist, you will be responsible for developing and optimizing AI solutions using tools like Claude.ai, Perplexity.ai, and other Anthropics-powered systems. Your primary focus will be on building and integrating AI-driven features into EdTech platforms to enhance adaptive learning, content personalization, and intelligent tutoring capabilities. In the realm of EdTech solutions development, you will design AI applications specifically tailored to the education sector. This includes creating virtual tutors, automated assessments, and recommendation systems. It will be crucial for you to collaborate closely with educators and curriculum designers to ensure that the AI functionalities align with educational goals effectively. Your role will also involve model training and fine-tuning, where you will be required to train and optimize LLMs for specific EdTech use cases. This process aims to guarantee the delivery of accurate and meaningful interactions. Additionally, you will apply transfer learning techniques to customize general AI models for education-specific tasks. Utilizing tools like Claude.ai and Perplexity.ai will be essential in your work to create innovative solutions for interactive learning and derive data-driven insights. You will have the opportunity to experiment with features from emerging Anthropics technologies to enhance the capabilities of the EdTech platform continually. Staying updated on the latest developments in AI and EdTech will be a crucial aspect of your role to implement cutting-edge solutions effectively. Engaging in exploratory research to explore how advanced AI tools can address key challenges in the education sector will also be part of your responsibilities. Collaboration and stakeholder engagement will play a significant role in your work, requiring you to work closely with product managers, UX designers, and other developers to deliver AI-powered EdTech features successfully. You will need to effectively communicate AI concepts and capabilities to technical and non-technical stakeholders, ensuring a clear understanding across the board. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. would be advantageous. Demonstrated expertise in working with Claude.ai, Perplexity.ai, and other Anthropics systems is essential. Proficiency in Python and familiarity with AI frameworks like TensorFlow, PyTorch, and Hugging Face are required. A deep understanding of NLP techniques, LLM architectures, and transformer-based models is crucial. Experience with API integrations and deploying AI/ML models in production environments is necessary. Previous experience in developing AI solutions for educational platforms and knowledge of challenges in EdTech, including accessibility, data privacy (e.g., FERPA, GDPR), and scalability, will be beneficial for this role.,

As an AI Developer specializing in Large Language Models (LLMs) with a focus on EdTech, you will play a crucial role in developing cutting-edge AI solutions to revolutionize learning experiences and educational outcomes. You will work with tools like Claude.ai, Perplexity.ai, and Anthropics" AI systems to create innovative features that enhance adaptive learning, content personalization, and intelligent tutoring within EdTech platforms. Your responsibilities will include developing and integrating AI solutions, designing AI applications tailored to the education sector, training and fine-tuning LLMs for specific EdTech use cases, and leveraging AI tools to create interactive learning experiences. You will also stay updated on the latest advancements in AI and EdTech, conduct research on implementing state-of-the-art solutions, and collaborate with cross-functional teams to deliver AI-powered features. To excel in this role, you should have a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. will be advantageous. Your technical skills should encompass expertise in Claude.ai, Perplexity.ai, and Anthropics systems, proficiency in Python and AI frameworks like TensorFlow and PyTorch, and a deep understanding of NLP techniques and transformer-based models. Experience with API integrations and deploying AI/ML models in production environments is essential. Furthermore, your EdTech experience should demonstrate your ability to address challenges such as accessibility, data privacy regulations (e.g., FERPA, GDPR), and scalability within educational platforms. Strong analytical, problem-solving, and communication skills are required to effectively explain complex AI concepts to both technical and non-technical stakeholders. A collaborative mindset and a passion for leveraging AI to enhance education will set you up for success in this role. Preferred qualifications include familiarity with adaptive learning systems, gamification in education, or chatbot implementations, as well as experience working with cloud platforms like AWS, GCP, or Azure. Prior involvement in projects involving real-time interactions through AI integration will be beneficial for this position.,

You are looking for a Lead AI Engineer with at least 8 years of experience to join UST at Trivandrum. As a Lead AI Engineer, you will be responsible for designing and implementing end-to-end AI/ML solutions using Python and deep learning frameworks like Keras. Your role will involve working with Generative AI and LLM architectures such as GPT-3 and BERT, as well as leading AI/ML teams and mentoring junior engineers. Your key responsibilities will include developing data pipelines and infrastructure using tools like Kafka, Big Data tools, Aurora DB, and ELK Stack. You will also be expected to deploy and optimize ML models on cloud platforms such as AWS, Azure, or GCP. Your expertise in Time Series Forecasting, Predictive Analytics, and Deep Learning will be crucial in translating business requirements into scalable AI solutions. In addition to hands-on experience in AI and Machine Learning, you should have a strong programming background in Python, Keras, and Pandas. Knowledge of advanced ML models like LangChain, GPT-3, and Transformers, as well as analytical models such as Time Series Forecasting, will be highly beneficial. Familiarity with databases like ChromaDB/Pinecone is also desired. Experience with PoC creation, model experimentation, and AI governance principles will be an advantage. You should also keep abreast of emerging trends and tools in the AI/ML space to evaluate their strategic fit and contribute to AI roadmap planning. UST is a global digital transformation solutions provider known for partnering with leading companies to drive real impact through innovation. With a workforce of over 30,000 employees in 30 countries, UST is committed to embedding innovation and agility into its clients" organizations, touching billions of lives in the process.,

Independently design, develop, and implement machine learning and NLP models. Build and fine-tune LLM-based solutions (prompt engineering, few-shot prompting, chain of thought prompting). Develop robust, production-quality code for AI/ML applications using Python. Build, deploy, and monitor models using AWS services (SageMaker, Bedrock, Lambda, etc.). Conduct data cleaning, feature engineering, and model evaluation on large datasets. Experiment with new GenAI tools, LLM architectures, and APIs (HuggingFace, LangChain, OpenAI, etc.). Collaborate with senior data scientists for reviews but own end-to-end solutioning tasks. Document models, pipelines, experiments, and results clearly and systematically. Stay updated with the latest in AI/ML, GenAI, and cloud technologies.

As a Senior Data Scientist specializing in Generative AI at our organization, you will play a crucial role in driving technical innovation and delivering impactful results within a team setting. You will be responsible for working with financial data, applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and troubleshooting and debugging GenAI models in production. To excel in this role, you must possess a Master's degree in Computer Science, Data Science, or a related field, with a Ph.D. being preferred. You should have 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI. Additionally, you should have demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. You must stay up-to-date with the rapidly evolving GenAI landscape, continuously learn and explore new tools and techniques, and effectively communicate technical concepts to non-technical stakeholders. Proficiency in Python, along with expertise in key libraries for AI/ML and GenAI applications such as TensorFlow, PyTorch, and Transformers, is mandatory. Experience in designing and implementing scalable API architectures for GenAI applications, along with a deep understanding of Machine Learning concepts, is essential. Preferred qualifications for this role include experience with MLOps, cloud computing platforms, conversational AI solutions, and contributions to research and publications in the field of Generative AI. As a Senior Data Scientist, you will be expected to demonstrate strong technical leadership and mentorship skills, as well as excellent communication and collaboration abilities. This job description provides a comprehensive overview of the responsibilities and qualifications required for the Senior Data Scientist position. If you are a highly motivated individual with a strong passion for Generative AI and possess the necessary technical skills and experience, we encourage you to apply for this role.,

Required Skills & Experience: 4+ years of experience in penetration testing, red teaming or offensive security. 1+ years working with AI/ML or LLM-based systems. Deep familiarity with LLM architectures (e.g., GPT, Claude, Mistral, LLaMA) and pipelines (e.g., LangChain, Haystack, RAG-as-a-Service). Strong understanding of embedding models, vector databases (Pinecone, Weaviate, FAISS), and API-based model deployments. Experience with adversarial ML, secure inference, and data integrity in training pipelines. Experience with red team infrastructure and tooling such as Cobalt Strike, Mythic, Sliver, Covenant, and custom payload development. Proficient in scripting languages such as Python, PowerShell, Bash or Go.

Across India (Noida, Pune, Hyderabad, Chennai and Banglore) Full time Skill & Experience 11+ years of experience preferred. Advanced degree in computer science, data science, or a related field. Deep understanding of LLM architectures, algorithms, and techniques. Strong experience in Python, SQL. Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) Experience with data labeling and annotation tools. Certifications in cloud platforms or ML technologies can be a plus. Proficient knowledge of cloud platforms (AWS, GCP, Azure). Strong problem-solving and analytical skills. Ability to work in team-oriented, collaborative environment.

Role : Principal Data Scientist / LLM Specialist Responsibilities : Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question answering is must. Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) Experience with data labeling and annotation tools. Certifications in cloud platforms or ML technologies can be a plus. Proficient knowledge of cloud platforms (AWS, GCP, Azure). Strong problem solving and analytical skills. Ability to work in team oriented, collaborative environment.Keywords : Data Scientist Statistician Data Engineer Python R Supervised & Unsupervised learning Machine Learning Algorithms Deep Learning Hugging Face Natural Language Processing (NLP) Computer Vision TensorFlow PyTorch Scikit learn Transformers LLM Frameworks LLM Models GPT 3, 4o BERT Llama

Hiring GenAI Python Developer with experience range 3 to 8 Years of experience Mandatory Skills: Python, LangChain techniques, LLM architectures, GPT, BERT, Streamlit, RAG mechanism Education: Btech/BE, BCA/MCA,Bsc/MSc