5 Huggingface Transformers Jobs

At PwC, our data and analytics team focuses on utilizing data to drive insights and support informed business decisions. We leverage advanced analytics techniques to assist clients in optimizing their operations and achieving strategic goals. As a data analysis professional at PwC, your role will involve utilizing advanced analytical methods to extract insights from large datasets, enabling data-driven decision-making. Your expertise in data manipulation, visualization, and statistical modeling will be pivotal in helping clients solve complex business challenges. PwC US - Acceleration Center is currently seeking a highly skilled MLOps/LLMOps Engineer to play a critical role in deploying, scaling, and maintaining Generative AI models. This position requires close collaboration with data scientists, ML/GenAI engineers, and DevOps teams to ensure the seamless integration and operation of GenAI models within production environments at PwC and for our clients. The ideal candidate will possess a strong background in MLOps practices and a keen interest in Generative AI technologies. With a preference for candidates with 4+ years of hands-on experience, core qualifications for this role include: - 3+ years of experience developing and deploying AI models in production environments, alongside 1 year of working on proofs of concept and prototypes. - Proficiency in software development, including building and maintaining scalable, distributed systems. - Strong programming skills in languages such as Python and familiarity with ML frameworks like TensorFlow and PyTorch. - Knowledge of containerization and orchestration tools like Docker and Kubernetes. - Understanding of cloud platforms such as AWS, GCP, and Azure, including their ML/AI service offerings. - Experience with continuous integration and delivery tools like Jenkins, GitLab CI/CD, or CircleCI. - Familiarity with infrastructure as code tools like Terraform or CloudFormation. Key Responsibilities: - Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. - Design and manage CI/CD pipelines specialized for ML workflows, including deploying generative models like GANs, VAEs, and Transformers. - Monitor and optimize AI model performance in production, utilizing tools for continuous validation, retraining, and A/B testing. - Collaborate with data scientists and ML researchers to translate model requirements into scalable operational frameworks. - Implement best practices for version control, containerization, and orchestration using industry-standard tools. - Ensure compliance with data privacy regulations and company policies during model deployment. - Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. - Stay updated with the latest MLOps and Generative AI developments to enhance AI capabilities. Project Delivery: - Design and implement scalable deployment pipelines for ML/GenAI models to transition them from development to production environments. - Oversee the setup of cloud infrastructure and automated data ingestion pipelines to meet GenAI workload requirements. - Create detailed documentation for deployment pipelines, monitoring setups, and operational procedures. Client Engagement: - Collaborate with clients to understand their business needs and design ML/LLMOps solutions. - Present technical approaches and results to technical and non-technical stakeholders. - Conduct training sessions and workshops for client teams. - Create comprehensive documentation and user guides for clients. Innovation And Knowledge Sharing: - Stay updated with the latest trends in MLOps/LLMOps and Generative AI. - Develop internal tools and frameworks to accelerate model development and deployment. - Mentor junior team members and contribute to technical publications. Professional And Educational Background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA,

Job Description: As a Data Scientist at Hitachi Solutions India Pvt Ltd in Pune, India, you will be a valuable member of our dynamic team. Your primary responsibility will be to extract valuable insights from complex datasets, develop advanced analytical models, and drive data-driven decision-making across the organization. With 8-14 years of experience, your primary skills should include Data Science, with secondary skills in Data Engineering/Data Analytics. You will play a pivotal role in working on cutting-edge AI applications with a focus on Natural Language Processing (NLP), Time Series Forecasting, and a working knowledge of Computer Vision (CV) techniques. Your role will involve collaborating with a diverse team of engineers, analysts, and domain experts to build holistic, multi-modal solutions. Your expertise in Python and libraries like Pandas, NumPy, Scikit-learn, HuggingFace Transformers, and Prophet/ARIMA will be essential. Additionally, you should have a strong understanding of the model development lifecycle, from data ingestion to deployment, and hands-on experience with SQL and data visualization tools like Seaborn, Matplotlib, and Tableau. Experience in handling retail-specific data, familiarity with cloud platforms like AWS, GCP, or Azure, and exposure to API development (FastAPI, Flask) for ML model deployment will be beneficial. Knowledge of MLOps practices, previous experience in fine-tuning language models, and expertise in Data Engineering using Azure technologies are desirable skills for this role. Key responsibilities will include applying NLP techniques to extract insights from text data, analyzing historical demand data for Time Series Forecasting, and potentially contributing to Computer Vision projects. Collaboration with cross-functional teams and developing scalable ML components for production environments will be crucial aspects of your role. Qualifications required for this position include a Master's degree in Computer Science, Data Science, Statistics, or a related field, proven experience in data science or machine learning, strong proficiency in Python and SQL, and familiarity with cloud technologies like Azure Databricks and MLflow. Excellent problem-solving skills, strong communication abilities, and the capability to work independently and collaboratively in a fast-paced environment are essential for success in this role. Please be cautious of potential scams during the recruitment process, and all official communication regarding your application and interview requests will be from our @hitachisolutions.com domain email address.,

As an AI Automation Specialist, you will play a crucial role in driving productivity optimization through the implementation of AI-powered solutions. Your responsibilities will include identifying opportunities to automate repetitive processes, enhance efficiency, and streamline workflows across various teams. You will be tasked with developing and executing automation strategies utilizing RPA, AI, and low-code/no-code tools to eliminate operational bottlenecks and enhance business operations. Collaborating closely with business leaders, product managers, and technology teams will be a key aspect of your role to drive AI transformation initiatives and ensure the successful scaling of automation impact. You will also be responsible for conducting change management activities, educating teams on AI-driven automation, and facilitating the seamless adoption of new processes within the organization. In addition, you will be involved in the deployment and management of AI tools such as NLP models, chatbots, document automation, and workflow optimization solutions. Working alongside cross-functional teams, you will assess pain points, design automation solutions, and implement AI-enabled productivity enhancements to drive continuous improvements and support strategic decision-making through data-driven analytics. Required Technical Skills: - Familiarity with low-code/no-code automation platforms like Bubble, Zapier AI, Make, Gumloop, n8n - Basic understanding of backend implementation including API integrations, Python, and JavaScript - Experience with video editing and graphic editing tools such as Heygen and Synthesia - Ability to build standalone apps using platforms like Replit and Lovable - Hands-on experience in NLP tools, chatbot development, and workflow automation - Strong understanding of data analytics and visualization tools like Power BI, Tableau, and Python - Proficiency in AI/ML tools (e.g., TensorFlow, Langgraph, HuggingFace Transformers) - Knowledge of AI tools for data science productivity (e.g., Cursor, Claude Code, H2O.ai, Windsurf, Copilot) Required Soft Skills: - Problem-solving mindset with the ability to identify inefficiencies and design AI-driven automation solutions - Leadership skills to influence senior leaders and drive impactful projects - Excellent communication and collaboration abilities to work effectively with cross-functional teams and stakeholders - Project management experience in implementing AI/automation projects with measurable impact.,

You are seeking a hands-on backend expert to elevate your FastAPI-based platform to the next level by developing production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. In this role, you will be responsible for various key areas: 1. Core Backend Enhancements: - Building APIs - Strengthening security with OAuth2/JWT, rate-limiting, SecretManager, and enhancing observability through structured logging and tracing - Adding CI/CD, test automation, health checks, and SLO dashboards 2. Awesome UI Interfaces: - Developing UI interfaces using React.js/Next.js, Redact/Context, and various CSS frameworks like Tailwind, MUI, Custom-CSS, and Shadcn 3. LLM & Agentic Services: - Designing micro/mini-services to host and route to platforms such as OpenAI, Anthropic, local HF models, embeddings & RAG pipelines - Implementing autonomous/recursive agents that orchestrate multi-step chains for Tools, Memory, and Planning 4. Model-Inference Infrastructure: - Setting up GPU/CPU inference servers behind an API gateway - Optimizing throughput with techniques like batching, streaming, quantization, and caching using tools like Redis and pgvector 5. NLP & Data Services: - Managing the NLP stack with Transformers for classification, extraction, and embedding generation - Building data pipelines to combine aggregated business metrics with model telemetry for analytics You will be working with a tech stack that includes Python, FastAPI, Starlette, Pydantic, Async SQLAlchemy, Postgres, Docker, Kubernetes, AWS/GCP, Redis, RabbitMQ, Celery, Prometheus, Grafana, OpenTelemetry, and more. Experience in building production Python REST APIs, SQL schema design in Postgres, async patterns & concurrency, UI application development, RAG, LLM/embedding workflows, cloud container orchestration, and CI/CD pipelines is essential for this role. Additionally, experience with streaming protocols, NGINX Ingress, SaaS security hardening, data privacy, event-sourced data models, and other related technologies would be advantageous. This role offers the opportunity to work on evolving products, tackle real challenges, and lead the scaling of AI services while working closely with the founder to shape the future of the platform. If you are looking for meaningful ownership and the chance to solve forward-looking problems, this role could be the right fit for you.,

At PwC, we focus on leveraging data to drive insights and make informed business decisions in the field of data and analytics. Our team utilises advanced analytics techniques to help clients optimize their operations and achieve their strategic goals. As a Data Analyst at PwC, you will play a crucial role in utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Your responsibilities will include leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. We are currently seeking a highly skilled MLOps/LLMOps Engineer to join PwC US - Acceleration Center. In this role, you will be responsible for the deployment, scaling, and maintenance of Generative AI models. Working closely with data scientists, ML/GenAI engineers, and DevOps teams, you will ensure seamless integration and operation of GenAI models within production environments at PwC and our clients. The ideal candidate will have a strong background in MLOps practices, coupled with experience and interest in Generative AI technologies. As a candidate, you should have a minimum of 4+ years of hands-on experience. Core qualifications for this role include 3+ years of experience developing and deploying AI models in production environments, with a year of experience in developing proofs of concept and prototypes. Additionally, a strong background in software development, proficiency in programming languages like Python, knowledge of ML frameworks and libraries, familiarity with containerization and orchestration tools, and experience with cloud platforms and CI/CD tools are essential. Key responsibilities of the role involve developing and implementing MLOps strategies tailored for Generative AI models, designing and managing CI/CD pipelines specialized for ML workflows, monitoring and optimizing the performance of AI models in production, collaborating with data scientists and ML researchers, and ensuring compliance with data privacy regulations. You will also be responsible for troubleshooting and resolving issues related to ML model serving, data anomalies, and infrastructure performance. The successful candidate will be proficient in MLOps tools such as MLflow, Kubeflow, Airflow, or similar, have expertise in generative AI frameworks, containerization technologies, MLOps and LLMOps practices, and cloud-based AI services. Nice-to-have qualifications include experience with advanced GenAI applications, familiarity with experiment tracking tools, knowledge of high-performance computing techniques, and contributions to open-source MLOps or GenAI projects. In addition to technical skills, the role requires project delivery capabilities such as designing scalable deployment pipelines for ML/GenAI models, overseeing cloud infrastructure setup, and creating detailed documentation for deployment pipelines. Client engagement is another essential aspect, involving collaboration with clients to understand their business needs, presenting technical approaches and results, conducting training sessions, and creating user guides for clients. To stay ahead in the field, you will need to stay updated with the latest trends in MLOps/LLMOps and Generative AI, apply this knowledge to improve existing systems and processes, develop internal tools and frameworks, mentor junior team members, and contribute to technical publications. The ideal candidate for this position should hold any graduate/BE/B.Tech/MCA/M.Sc/M.E/M.Tech/Masters Degree/MBA. Join us at PwC and be part of a dynamic team driving innovation in data and analytics!,