319 Quantization Jobs - Page 13

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Exp: 22+yrs Location: Pune/Chennai/Mumbai/Bangalore NP: Immediate joiner – 30days Job Description: GenAI & Data Science; Digital Architecture & Enablement; Emerging Tech & Innovation Evangelist Principles and workings of generative models. Knowledge of saving and loading AI models, such as using formats like ONNX or native formats of deep learning frameworks. Cloud platforms like AWS, GCP, or Azure, especially services related to AI and ML. Containerization tools like Docker to package the application and its dependencies. GPUs, TPUs, or other accelerators, and how to leverage them for AI inference. Techniques like model quantization, pruning, and distillation to improve inference speed and reduce memory footprint. Distribute incoming application traffic across multiple instances to ensure optimal resource utilization. Set up monitoring tools to track the health, uptime, and performance of the deployed application. Secure deployment of applications, including encryption, authentication, and authorization mechanisms. Data protection principles, especially when handling user data or other sensitive information. Proficiency with tools like Git. CI/CD pipelines and tools like Jenkins, Travis CI, or GitHub Actions. Networking principles to ensure the application is accessible and communicates effectively with other services or databases. Integrating databases to store or retrieve data, especially if the AI application requires real-time data access. Job Location: BangaloreChennaiMumbaiPune

AI Developer Intern (WFO) Location: Hyderabad (T-Hub) About Altibbe Health Pvt. Ltd.: Altibbe Health is a health-tech company committed to leveraging Artificial Intelligence to improve accessibility, transparency, and decision-making in healthcare products. Role Overview: We are looking for an AI Engineer who brings together strong technical foundations in Machine Learning , Generative AI , and Document Intelligence . You will work on AI systems that process healthcare-related documents, extract key insights, and generate human-like responses and reports. This is a high-impact role that directly supports Altibbe’s mission to transform healthcare data into meaningful intelligence. Key Responsibilities: Develop and fine-tune LLMs and summarization models for healthcare documentation and product transparency reports. Build automated document pipelines (PDF, DOCX, OCR) for extracting and transforming structured/unstructured health data. Create domain-specific question generators, keyword extractors, and summary systems using advanced NLP techniques. Integrate AI models into scalable web applications using Streamlit , Flask , or React . Implement secure user authentication and API protection for production apps. Collaborate with internal teams to define product requirements and AI model capabilities. Continuously optimize model performance, inference speed, and cost using techniques like quantization , LoRA , and bitsandbytes . Required Skills & Experience: Proficiency in Python , with strong experience in Pandas , PyTorch , and HuggingFace Transformers . Deep understanding of Generative AI , prompt engineering , and LLM fine-tuning . Hands-on with OCR , text summarization , keyword extraction , and document parsing. Experience deploying full-stack ML apps using Streamlit , Flask , or React + MongoDB . Knowledge of secure backend development and production-level authentication practices . Comfortable with version control ( Git ) and collaborative development. Preferred Qualifications: Experience in healthcare or pharma-tech AI solutions. Prior hackathon achievements and open-source contributions. What We Offer: Opportunity to impact healthcare AI in a meaningful way Pathway to a permanent role based on performance Opportunity to grow with autonomy and real world experience Join Us If you're passionate about AI for good, and love building end-to-end systems that solve real healthcare challenges — Altibbe Health Pvt. Ltd. is the place for you. Job Types: Internship, Contractual / Temporary Contract length: 3 months Pay: ₹12,000.00 - ₹15,000.00 per month Schedule: Day shift Ability to commute/relocate: Gachibowli, Hyderabad, Telangana: Reliably commute or planning to relocate before starting work (Preferred) Application Question(s): Do you have prior experience in AI Development ? Location: Gachibowli, Hyderabad, Telangana (Preferred) Work Location: In person

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way. The Role : In this role you will be part of the Logitech Hardware Audio DSP and ML team developing and will be implementing real-time audio ML solutions to deliver innovative audio experiences to the customer. If you have a strong understanding of Audio DSP and TinyML apply for this role and have a huge contribution on the audio products that we develop! Your Contribution: Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will: Responsible for developing model and inference on resource constrained platforms like Tensilica DSP, ARM and RISCV cores.Responsible for optimizing and improving algorithm performance in real-world conditions – demonstrating innovative solutions to tough challenges.Work with cross-functional product team to deliver seamless customer audio experience. Key Qualifications: For consideration, you must bring the following minimum skills and experiences to our team: Experience leading a ML team with 10+ years of experience working in audio signal processing/ML.Tiny ML / Embedded ML - Hands-on experience porting neural network algorithms from intermediate representations such as Tensor Flow (TFLM), ONNX, etc. onto embedded targets using device-specific compilation tools and/or inference API’s.Deep understanding of on-device quantization techniques including post-training quantization, training-aware quantization, mixed precision inference.Strong programming skills in c, python.Conceptual understanding of how neural network operators map to embedded hardware accelerators such as DSP’s and NPU’s.Familiarity with Deep Learning Audio Signal Processing approaches for tasks including Speech enhancement / noise suppression / voice pickup Additional Skills: Experienced with Linux, Docker.Familiarity with CMSIS NN, HIFI NNLib is a plusFamiliarity with audio measurements and standard subjective/objective audio evaluation metrics.Experience working in hardware product teams from product concept to mass productionGood Audio listening skills and experience detecting audio artifacts.Experience communicating effectively in a cross functional environment. Strong problem-solving, critical-thinking skillsFamiliarity with code version control practices Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house. Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you! We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location. All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability. If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at +1-510-713-4866 for assistance and we will get back to you as soon as possible.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way. The Role : In this role you will be part of the Logitech Hardware Audio DSP and ML team developing and will be implementing real-time audio ML solutions to deliver innovative audio experiences to the customer. If you have a strong understanding of Audio DSP and TinyML apply for this role and have a huge contribution on the audio products that we develop! Your Contribution: Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will: Responsible for developing model and inference on resource constrained platforms like Tensilica DSP, ARM and RISCV cores.Responsible for optimizing and improving algorithm performance in real-world conditions – demonstrating innovative solutions to tough challenges.Work with cross-functional product team to deliver seamless customer audio experience. Key Qualifications: For consideration, you must bring the following minimum skills and experiences to our team: 7+ years of experience working in audio signal processing product teams.Tiny ML / Embedded ML - Hands-on experience porting neural network algorithms from intermediate representations such as Tensor Flow (TFLM), ONNX, etc. onto embedded targets using device-specific compilation tools and/or inference API’s.Deep understanding of on-device quantization techniques including post-training quantization, training-aware quantization, mixed precision inference.Strong programming skills in c, python.Conceptual understanding of how neural network operators map to embedded hardware accelerators such as DSP’s and NPU’s.Familiarity with Deep Learning Audio Signal Processing approaches for tasks including Speech enhancement / noise suppression / voice pickup Additional Skills: Experienced with Linux, Docker.Familiarity with CMSIS NN, HIFI NNLib is a plusFamiliarity with audio measurements and standard subjective/objective audio evaluation metrics.Experience working in hardware product teams from product concept to mass productionGood Audio listening skills and experience detecting audio artifacts.Experience communicating effectively in a cross functional environment. Strong problem-solving, critical-thinking skillsFamiliarity with code version control practices Education: Minimum Engineering degree in EE, CS or equivalent practical experience. Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house. Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you! We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location. All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability. If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at +1-510-713-4866 for assistance and we will get back to you as soon as possible.

ML Inference & Optimization Engineer Location: Mumbai, Experience: 2–4 years You will be responsible for deploying and scaling domain and task-specific LLMs and deep learning models for real-time and batch inference. You'll work on quantization, model optimizations, runtime tuning, and performance-critical serving. What You'll Do Integrate models into containerized services and APIs, and build high-performance inference pipelines optimized for latency, concurrency, and cost Deploy and optimize LLMs using vLLM, TGI, SGLang, Triton, TensorRT etc. Implement model quantization, speculative decoding, KV cache optimization, dynamic batching etc. Benchmark model throughput and latency across cloud VM configurations Debug performance bottlenecks: VRAM usage, token sampling speed, latency, instability Collaborate with infra team for scaling and observability Monitor and troubleshoot inference performance, ensuring system reliability and efficiency Stay abreast of advancements in model inference technologies and best practices You Bring 3+ years of experience in deploying and optimizing machine learning models in production, with 1+ years of experience in deploying deep learning models Experience deploying async inference APIs (FastAPI, gRPC, Ray Serve etc.) Understanding of PyTorch internals and inference-time optimization Familiarity with LLM runtimes: vLLM, TGI, TensorRT-LLM, ONNX Runtime etc. Familiarity with GPU profiling tools (nsight, nvtop), model quantization pipelines Bonus: prior work on ElasticSearch, distributed KV cache, or custom tokenizers Bachelor's degree in Computer Science, Engineering, or related field Show more Show less

Job Summary:We are seeking a skilled and innovative Data Scientist with a strong foundation in hyperparameter optimization, TensorFlow Lite, and IoT-based electronics. The ideal candidate will have experience in building and deploying efficient machine learning models on resource-constrained embedded devices. You will work closely with hardware, firmware, and software teams to optimize ML pipelines and enable intelligent edge solutions. Key Responsibilities:Develop and deploy ML models for embedded/IoT devices using TensorFlow Lite or similar frameworks.Design and run experiments to optimize model performance through hyperparameter tuning (Grid Search, Random Search, Bayesian Optimization, etc.).Work with cross-functional teams to integrate ML models into embedded systems and validate them on target hardware.Preprocess and analyze sensor/electronic data from IoT devices.Conduct performance evaluations (accuracy, latency, memory footprint) and ensure models meet hardware constraints.Automate training, validation, and deployment workflows using scripting and ML tools.Stay updated with emerging trends in TinyML, on-device learning, and efficient model architectures. Required Qualifications:Bachelor’s or Master’s degree in Computer Science, Electronics, Electrical Engineering, or a related field.3+ years of experience in applied machine learning or data science roles.Proficiency in Python, TensorFlow, and TensorFlow Lite.Strong understanding of hyperparameter optimization techniques and experience with relevant tools/libraries (Optuna, HyperOpt, Ray Tune, etc.).Good understanding of edge AI constraints (compute, memory, power consumption).Experience in preprocessing data from sensors such as accelerometers, gyros, temperature, etc.Familiarity with embedded development tools and debugging. Preferred Skills (Nice to Have):Knowledge of C/C++ for embedded systems.Experience with TinyML and model quantization/pruning techniques.Exposure to platforms like Edge Impulse, TensorFlow Lite Micro, or Arduino ML.Understanding of communication protocols (BLE, MQTT, LoRa, etc.). What We Offer:Work on cutting-edge AI for IoT projects with real-world impact.Collaborative and growth-oriented team environment.Competitive salary and benefits package.

Institute of Information Science Postdoctoral Researcher 2 Person The Computer Systems Laboratory - Machine Learning Systems Team Focuses On Research Areas Including Parallel And Distributed Computing, Compilers, And Computer Architecture. We Aim To Leverage Computer System Technologies To Accelerate The Inference And Training Of Deep Learning Models And Develop Optimizations For Next-generation AI Models. Our Research Emphasizes The Following Job DescriptionUnit Institute of Information ScienceJobTitle Postdoctoral Researcher 2 PersonWork Content Research on Optimization of Deep Learning Model Inference and Training AI Model Compression and Optimization Model Compression Techniques (e.g., Pruning And Quantization) Reduce The Size And Computational Demands Of AI Models, Which Are Crucial For Resource-constrained Platforms Such As Embedded Systems And Memory-limited AI Accelerators. We Aim To Explore AI compiler: deployment methods for compressed models across servers, edge devices, and heterogeneous systems. High performance computing: efficient execution of compressed models on processors with advanced AI extensions, e.g., Intel AVX512, ARM SVE, RISC-V RVV, and tensor-level accelerations on GPUs and NPUs. AI Accelerator Design We aim to design AI accelerators for accelerating AI model inference, focusing on software and hardware co-design and co-optimization. Optimization of AI Model Inference in Heterogeneous Environments Computer Architectures Are Evolving Toward Heterogeneous Multi-processor Designs (e.g., CPUs + GPUs + AI Accelerators). Integrating Heterogeneous Processors To Execute Complex Models (e.g., Hybrid Models, Multi-models, And Multi-task Models) With High Computational Efficiency Poses a Critical Challenge. We Aim To Explore Efficient scheduling algorithms. Parallel algorithms for the three dimensions: data parallelism, model parallelism, and tensor parallelism. Qualifications Ph.D. degree in Computer Science, Computer Engineering, or Electrical Engineering Experience in parallel computing and parallel programming (CUDA or OpenCL, C/C++ programming) or hardware design (Verilog or HLS) Proficient in system and software development Candidates With The Following Experience Will Be Given Priority Experience in deep learning platforms, including PyTorch, TensorFlow, TVM, etc. Experience in high-performance computing or embedded systems. Experience in algorithm designs. Knowledge of compilers or computer architectureWorking EnvironmentOperating Hours 8:30AM-5:30PMWork Place Institute of Information Science, Academia SinicaTreatment According to Academia Sinica standards: Postdoctoral Researchers: NT$64,711-99,317/month. Benefits include: labor and healthcare insurance, and year-end bonuses. Reference Site 洪鼎詠網頁: http://www.iis.sinica.edu.tw/pages/dyhong/index_zh.html, 吳真貞網頁: http://www.iis.sinica.edu.tw/pages/wuj/index_zh.html Please Email Your CV (including Publications, Projects, And Work Experience), Transcripts (undergraduate And Above), And Any Other Materials That May Assist In The Review Process To The Following PIs Acceptance MethodContacts Dr. Ding-Yong Hong Contact Address Room 818, New IIS Building, Academia Sinica Contact Telephone 02-27883799 ext. 1818Email dyhong@iis.sinica.edu.tw Required Documents Dr. Ding-Yong Hong: dyhong@iis.sinica.edu.tw Dr. Jan-Jan Wu: wuj@iis.sinica.edu.twPrecautions for application DatePublication Date 2025-01-20Expiration Date 2025-12-31

Responsibilities:Front-End Development: Design and implement user-friendly interfaces for AI applications. Utilize modern web frameworks (e.g., React, Vue.js) to create engaging user experiences. Optimize front-end performance and responsiveness.Back-End Development: Build scalable and efficient backend systems to support AI model deployment. Design and implement RESTful APIs for seamless communication between front-end and back-end. Integrate with cloud platforms (e.g., AWS, Azure) for infrastructure management.AI Model Development: Train and fine-tune state-of-the-art generative AI and LLM models. Leverage deep learning frameworks (e.g., TensorFlow, PyTorch) for model development. Implement efficient inference pipelines for real-time model predictions.Data Engineering: Design and maintain robust data pipelines for model training and evaluation. Preprocess and clean large-scale datasets for optimal model performance. Implement data versioning and monitoring strategies.Preferred Qualifications: Graduate degree in Computer Science, Artificial Intelligence, or a related field. 5+ years of experience in full-stack development. 2+ years of experience in AI model development, particularly with generative AI and LLMs. Strong understanding of machine learning algorithms and natural language processing. Proficiency in Python and relevant AI frameworks (e.g., TensorFlow, PyTorch). Skills: Excellent communication and collaboration skills. Ability to work independently and in a team environment. Passion for staying updated with the latest advancements in AI. Bonus Points: Experience in the Biopharma industry. Experience with model optimization techniques (e.g., quantization, pruning). Contributions to open-source AI projects. Publications in relevant AI conferences or journals.

Job Description: We are looking for a passionate and highly motivated Research Engineer to join our team and contribute to the advancement of Language Model capabilities. As part of our team, you will play an integral role in researching and implementing cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and other state-of-the-art methods to enhance the performance of our models. If you are excited about working on innovative technologies, fine-tuning models, and building scalable AI systems, this is the perfect opportunity for you! Key Responsibilities: Engage in research and implementation of Retrieval-Augmented Generation (RAG) and other advanced techniques to enhance Language model capabilities. Participate in data preparation for fine-tuning processes. Assist in setting up and optimizing the pipeline for fine-tuning, Quantization. Participate in the training of small transformer models, ensuring performance and efficiency. Contribute to the development of an internal orchestration framework for LLM. Collaborate with senior engineers to integrate LLM SW Components into the existing system architecture. Support the deployment and monitoring of models in production environments. Document processes, workflows, and findings to ensure knowledge sharing and reproducibility. Qualifications: Strong Python skills. Experience with Data Wrangling and Preprocessing. Familiarity with LangChain, LlamaIndex, and VectorDB. Good understanding of transformer architecture, embeddings, and tokenizers. Experience with machine learning frameworks like TensorFlow or PyTorch. Understanding of LLMs, fine-tuning techniques, and RAG methodologies. Proficiency in version control systems (e.g., Git) and software development best practices. This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth. Company: Airbus India Private Limited Employment Type: Internship - Experience Level: Student Job Family: Digital By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus. Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com . At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.