Gen AI Architect
Seattle, WA · On-site
HuggingFace Datasets, TensorFlow Datasets • LLMOps Proficiency • Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions • Monitoring & Management: Ray ...
Gen AI Architect
Seattle, WA · On-site
HuggingFace Datasets, TensorFlow Datasets • LLMOps Proficiency • Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions • Monitoring & Management: Ray ...
MLOps Engineer
Bellevue, WA · Remote
... PyTorch, HuggingFace Transformers and libraries (like scikit-learn, etc.). * 4-6 years of experience with ClassicAI/GenAI ML Model Operationalization in Production. * 4 to 6 years of strong ...
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MLOps Engineer
Bellevue, WA · Remote
... PyTorch, HuggingFace Transformers and libraries (like scikit-learn, etc.). * 4-6 years of experience with ClassicAI/GenAI ML Model Operationalization in Production. * 4 to 6 years of strong ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Responsibilities : • Implement quantized and sparse recipes in inference engines (vLLM, TRT-LLM, SGLang) • Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Responsibilities : • Implement quantized and sparse recipes in inference engines (vLLM, TRT-LLM, SGLang) • Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized ...
AI Scientist
Bellevue, WA · On-site
Preferred : • Experience and demonstrated capability to handle challenges with vague or abstract problem definition. • Experience with frameworks and tools such as DeepSpeed, HuggingFace ...
AI Scientist
Bellevue, WA · On-site
Preferred : • Experience and demonstrated capability to handle challenges with vague or abstract problem definition. • Experience with frameworks and tools such as DeepSpeed, HuggingFace ...
Gen AI Architect
Seattle, WA · On-site
$160K - $200K/yr
HuggingFace Datasets, TensorFlow Datasets - 3. LLMOps Proficiency - Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions - Monitoring & Management: Ray, SeldonCore ...
Gen AI Architect
Seattle, WA · On-site
$160K - $200K/yr
HuggingFace Datasets, TensorFlow Datasets - 3. LLMOps Proficiency - Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions - Monitoring & Management: Ray, SeldonCore ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized checkpoints serialize correctly for downstream serving * Build prototypes and benchmarking harnesses to evaluate ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized checkpoints serialize correctly for downstream serving * Build prototypes and benchmarking harnesses to evaluate ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized checkpoints serialize correctly for downstream serving * Build prototypes and benchmarking harnesses to evaluate ...
Senior Software Engineer, Quantized Inference
Redmond, WA · On-site
$137K - $180K/yr
Own model export pipelines (ModelOpt, Megatron-LM HuggingFace), ensuring quantized checkpoints serialize correctly for downstream serving * Build prototypes and benchmarking harnesses to evaluate ...
Machine Learning Engineer, Information Security
$142K - $263K/yr
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. Hands-on experience with full ML model lifecycle: from ...
Machine Learning Engineer, Information Security
$142K - $263K/yr
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. Hands-on experience with full ML model lifecycle: from ...
Software Engineer, Applied AI
Seattle, WA · On-site
Experience integrating LLMs or generative AI models into applications Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers * Must be able and willing to ...
Software Engineer, Applied AI
Seattle, WA · On-site
Experience integrating LLMs or generative AI models into applications Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers * Must be able and willing to ...
Distinguished, Data Scientist
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies - Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Distinguished, Data Scientist
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies - Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Director, Data Science
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies -- Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Director, Data Science
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies -- Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Gen AI Architect
Seattle, WA · On-site
HuggingFace Datasets, TensorFlow Datasets • LLMOps Proficiency • Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions • Monitoring & Management: Ray ...
Gen AI Architect
Seattle, WA · On-site
HuggingFace Datasets, TensorFlow Datasets • LLMOps Proficiency • Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions • Monitoring & Management: Ray ...
Machine Learning Engineer, Information Security
$142K - $263K/yr
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. Hands-on experience with full ML model lifecycle: from ...
Machine Learning Engineer, Information Security
$142K - $263K/yr
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. Hands-on experience with full ML model lifecycle: from ...
Director, Data Science
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies - Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Director, Data Science
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies - Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
ML Engineer (Senior)
Seattle, WA · On-site
$140K - $220K/yr
Advanced ML/AI frameworks and techniques (e.g., PyTorch Lightning, JAX, HuggingFace, ONNX optimizations) * Lower-level or performance-focused languages for ML acceleration (e.g., C++, Rust, CUDA)
ML Engineer (Senior)
Seattle, WA · On-site
$140K - $220K/yr
Advanced ML/AI frameworks and techniques (e.g., PyTorch Lightning, JAX, HuggingFace, ONNX optimizations) * Lower-level or performance-focused languages for ML acceleration (e.g., C++, Rust, CUDA)
Software Engineer, Applied AI
Seattle, WA · On-site
$166K - $203K/yr
Experience integrating LLMs or generative AI models into applications Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers * Must be able and willing to ...
Software Engineer, Applied AI
Seattle, WA · On-site
$166K - $203K/yr
Experience integrating LLMs or generative AI models into applications Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers * Must be able and willing to ...
Distinguished, Data Scientist
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies -- Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Distinguished, Data Scientist
Bellevue, WA · On-site
$156K - $312K/yr
Extensive hands-on experience of a broad stack of technologies -- Python, Huggingface, VectorDB, Tensorflow, Pytorch, ElasticSearch, Azure, etc. * Authored research publications in top peer-reviewed ...
Huggingface information
What are the key skills and qualifications needed to thrive in the Huggingface position, and why are they important?
To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.
What does a typical day look like for an engineer working at Hugging Face?
As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.
What is a Huggingface job?
A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.
What cities near Redmond, WA are hiring for Huggingface jobs? Cities near Redmond, WA with the most Huggingface job openings:
Tata Consultancy Services rating
6.5
Based on 21 frontline employees who took The Breakroom Quiz
159th of 210 rated it services
Job description
Job Summary:
Tata Consultancy Services is seeking a Gen AI Architect to lead innovative machine learning solutions. The role involves developing GenAI applications, educating teams on best practices, and driving the delivery of reliable solutions while championing teamwork and effective communication across various levels of management.
Responsibilities:
• Be an expert source on machine learning to drive delivery of new and innovative solutions.
• Propose creative solutions to approach business solutions with emerging technologies.
• Prototype new ways of applying technologies for solving business problems.
• Educate others so that they can demonstrate the innovative methods for achieving outcomes.
• Build and maintain machine learning principles, best practices, and code accelerators.
• Conduct external research and internal experimentation for machine learning techniques.
• Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork.
• Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management.
• GenAI Application Development Expertise
• Programming Languages: Python
• Development Tools: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise
• Techniques: RAG Techniques
• Databases: Vector Databases (Pinecone, Weaviate, Qdrant)
• Additional Technologies: Knowledge Graphs, FastAPI, Streamlit, Gradio
• Domain Model Fine-Tuning Capabilities
• Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
• Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
• Datasets: HuggingFace Datasets, TensorFlow Datasets
• LLMOps Proficiency
• Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
• Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
• Data Engineering for AI Applications
• Data Processing & Management: Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake
• Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
• Data Catalogs: Amundsen, Collibra, Alation
• AI-Ready Cybersecurity Knowledge
• Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
• Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
• GenAI Guardrails and Ethics
• Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
• Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
• Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
• Lead a team of junior developers
• Ability to translate requirements into understandable technical design.
• Task effort estimation and distribution among team members.
• Excellent communication skills, and stakeholder management.
• Ability to work with Cross functional teams and business users.
Qualifications:
Required:
• Be an expert source on machine learning to drive delivery of new and innovative solutions.
• Propose creative solutions to approach business solutions with emerging technologies.
• Prototype new ways of applying technologies for solving business problems.
• Educate others so that they can demonstrate the innovative methods for achieving outcomes.
• Build and maintain machine learning principles, best practices, and code accelerators.
• Conduct external research and internal experimentation for machine learning techniques.
• Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork.
• Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management.
• GenAI Application Development Expertise
• Programming Languages: Python
• Development Tools: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise
• Techniques: RAG Techniques
• Databases: Vector Databases (Pinecone, Weaviate, Qdrant)
• Additional Technologies: Knowledge Graphs, FastAPI, Streamlit, Gradio
• Domain Model Fine-Tuning Capabilities
• Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
• Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
• Datasets: HuggingFace Datasets, TensorFlow Datasets
• LLMOps Proficiency
• Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
• Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
• Data Engineering for AI Applications
• Data Processing & Management: Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake
• Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
• Data Catalogs: Amundsen, Collibra, Alation
• AI-Ready Cybersecurity Knowledge
• Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
• Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
• GenAI Guardrails and Ethics
• Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
• Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
• Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
• Bachelor’s degree in computer science, Data Science, or a related field; master’s degree preferred.
• 5+ years of professional and/or postgraduate academic research experience in software engineering.
• 4+ year of experience designing and developing machine learning solutions.
• 3+ years of experience with cloud native engineering, AWS, Azure, Google.
• Lead a team of junior developers
• Ability to translate requirements into understandable technical design.
• Task effort estimation and distribution among team members.
• Excellent communication skills, and stakeholder management.
• Ability to work with Cross functional teams and business users.
Preferred:
• Preferred experience in SAP / Salesforce or Oracle programs.
Company:
Tata Consultancy Services is a business solutions company that specializes on information technology services and consulting. It is a sub-organization of Tata Group. Founded in 1968, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.
Tata Consultancy Services is seeking a Gen AI Architect to lead innovative machine learning solutions. The role involves developing GenAI applications, educating teams on best practices, and driving the delivery of reliable solutions while championing teamwork and effective communication across various levels of management.
Responsibilities:
• Be an expert source on machine learning to drive delivery of new and innovative solutions.
• Propose creative solutions to approach business solutions with emerging technologies.
• Prototype new ways of applying technologies for solving business problems.
• Educate others so that they can demonstrate the innovative methods for achieving outcomes.
• Build and maintain machine learning principles, best practices, and code accelerators.
• Conduct external research and internal experimentation for machine learning techniques.
• Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork.
• Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management.
• GenAI Application Development Expertise
• Programming Languages: Python
• Development Tools: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise
• Techniques: RAG Techniques
• Databases: Vector Databases (Pinecone, Weaviate, Qdrant)
• Additional Technologies: Knowledge Graphs, FastAPI, Streamlit, Gradio
• Domain Model Fine-Tuning Capabilities
• Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
• Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
• Datasets: HuggingFace Datasets, TensorFlow Datasets
• LLMOps Proficiency
• Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
• Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
• Data Engineering for AI Applications
• Data Processing & Management: Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake
• Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
• Data Catalogs: Amundsen, Collibra, Alation
• AI-Ready Cybersecurity Knowledge
• Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
• Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
• GenAI Guardrails and Ethics
• Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
• Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
• Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
• Lead a team of junior developers
• Ability to translate requirements into understandable technical design.
• Task effort estimation and distribution among team members.
• Excellent communication skills, and stakeholder management.
• Ability to work with Cross functional teams and business users.
Qualifications:
Required:
• Be an expert source on machine learning to drive delivery of new and innovative solutions.
• Propose creative solutions to approach business solutions with emerging technologies.
• Prototype new ways of applying technologies for solving business problems.
• Educate others so that they can demonstrate the innovative methods for achieving outcomes.
• Build and maintain machine learning principles, best practices, and code accelerators.
• Conduct external research and internal experimentation for machine learning techniques.
• Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork.
• Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management.
• GenAI Application Development Expertise
• Programming Languages: Python
• Development Tools: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise
• Techniques: RAG Techniques
• Databases: Vector Databases (Pinecone, Weaviate, Qdrant)
• Additional Technologies: Knowledge Graphs, FastAPI, Streamlit, Gradio
• Domain Model Fine-Tuning Capabilities
• Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
• Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
• Datasets: HuggingFace Datasets, TensorFlow Datasets
• LLMOps Proficiency
• Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
• Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
• Data Engineering for AI Applications
• Data Processing & Management: Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake
• Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
• Data Catalogs: Amundsen, Collibra, Alation
• AI-Ready Cybersecurity Knowledge
• Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
• Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
• GenAI Guardrails and Ethics
• Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
• Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
• Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
• Bachelor’s degree in computer science, Data Science, or a related field; master’s degree preferred.
• 5+ years of professional and/or postgraduate academic research experience in software engineering.
• 4+ year of experience designing and developing machine learning solutions.
• 3+ years of experience with cloud native engineering, AWS, Azure, Google.
• Lead a team of junior developers
• Ability to translate requirements into understandable technical design.
• Task effort estimation and distribution among team members.
• Excellent communication skills, and stakeholder management.
• Ability to work with Cross functional teams and business users.
Preferred:
• Preferred experience in SAP / Salesforce or Oracle programs.
Company:
Tata Consultancy Services is a business solutions company that specializes on information technology services and consulting. It is a sub-organization of Tata Group. Founded in 1968, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.
What Tata Consultancy Services employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Tata Consultancy Services
Sourced by ZipRecruiter
Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT, BPO, infrastructure, engineering, and assurance services. This is delivered through its unique Global Network Delivery Model™, recognized as the benchmark of excellence in software development. TCS delivers a level of certainty that no other firm can match--to our clients and to our employees. Come join us and experience certainty in your career. TCS a global Consulting and IT Services firm that is ranked in the top quartile by industry analysts. Our 2021 fiscal revenues topped $25 B and our market capitalization is over $170+B, yet we have a deep and large history of philanthropy and corporate social responsibility. Now approaching 600K of the best IT professionals and consultants, we are a trusted advisor, guiding our clients' enterprises through growth and transformation journeys - helping them to become agile, intelligent, automated and on the cloud. We are devoted to DEI and are recognized as a top employer and place to work.