BharatGen

About Us: We are seeking a talented and passionate Applied AI/ML Engineer to join our team. In this role, you will spearhead the end-to-end lifecycle of foundational model development, employing state-of-the-art approaches in generative AI. Your role will entail focus on data- and compute-efficient learning approaches to tackle challenges characteristics to Indian context. Your responsibilities will include optimizing model training and inference pipelines, production ready model deployment, ensuring scalability through distributed systems, and fine-tuning models on domain adaptation. You will collaborate with cross-functional teams to build robust AI stacks and integrate them seamlessly into production pipelines. Beyond research and experimentation, you will play a pivotal role in transforming state-of-the-art models into operational systems that deliver measurable impact. As a leader in this domain, you will collaborate with other technical team members and subject matter experts, document technical processes, and maintain clear, organized codebases to support innovation and reproducibility. This role is ideal for proactive individuals passionate about driving transformative advancements in generative AI and scaling solutions for real-world impact. Key Responsibilities: Development and training of foundational models across modalities End to end lifecycle management of foundational model development from data curation to model deployment by collaborating with the core team members Conduct research to advance model accuracy and efficiency. Implement state-of-the-art AI techniques in Text/Speech and language processing. Collaborate with cross-functional teams to build robust AI stacks and integrate them seamlessly into production pipelines. Develop pipelines for debugging, CI/CD and observability of the development process. Demonstrated ability to lead projects and provide innovative solutions. Should document technical processes, model architectures, and experimental results., maintain clear and organized code repositories. Education Qualification: Bachelor’s or Master’sin any related field with 2 to 5 years of experience in industry in applied AI/ML. Minimum Requirements: Proficiency in Python programming and familiarity with 3-4 from the list of toolsspecified below: 1. Foundational model libraries and frameworks (TensorFlow, PyTorch, HF Transformers, NeMo, etc) 2. Experience with distributed training (SLURM, Ray, Pytorch DDP, Deepspeed, NCCL, etc) 3. Inference servers(vLLM) 4. Version controlsystems and observability (Git, DVC, MLFlow, W&B, KubeFlow) 5. Data analysis and curation tools(Dask, Milvus, Apache Spark, Numpy) 6. Text-to-Speech tools (Whisper, Voicebox, VALL-E (X), HuBERT/Unitspeech) 7. LLMOPs Tools, Dockers etc 8. Hands on experience with AI application libraries and frameworks (DSPy, Langgraph, langchain, llamaindex etc.)

About Us: We are seeking a talented and passionate Applied AI/ML Engineer to join our team. In this role, you will spearhead the end-to-end lifecycle of foundational model development, employing state-of-the-art approaches in generative AI. Your role will entail focus on data- and compute-efficient learning approaches to tackle challenges characteristics to Indian context. Your responsibilities will include optimizing model training and inference pipelines, production ready model deployment, ensuring scalability through distributed systems, and fine-tuning models on domain adaptation. You will collaborate with cross-functional teams to build robust AI stacks and integrate them seamlessly into production pipelines. Beyond research and experimentation, you will play a pivotal role in transforming state-of-the-art models into operational systems that deliver measurable impact. As a leader in this domain, you will collaborate with other technical team members and subject matter experts, document technical processes, and maintain clear, organized codebases to support innovation and reproducibility. This role is ideal for proactive individuals passionate about driving transformative advancements in generative AI and scaling solutions for real-world impact. Key Responsibilities: Development and training of foundational models across modalities End to end lifecycle management of foundational model development from data curation to model deployment by collaborating with the core team members Conduct research to advance model accuracy and efficiency. Implement state-of-the-art AI techniques in Text/Speech and language processing. Collaborate with cross-functional teams to build robust AI stacks and integrate them seamlessly into production pipelines. Develop pipelines for debugging, CI/CD and observability of the development process. Demonstrated ability to lead projects and provide innovative solutions. Should document technical processes, model architectures, and experimental results., maintain clear and organized code repositories. Education Qualification: Bachelors or Mastersin any related field with 2 to 5 years of experience in industry in applied AI/ML. Minimum Requirements: Proficiency in Python programming and familiarity with 3-4 from the list of toolsspecified below: 1. Foundational model libraries and frameworks (TensorFlow, PyTorch, HF Transformers, NeMo, etc) 2. Experience with distributed training (SLURM, Ray, Pytorch DDP, Deepspeed, NCCL, etc) 3. Inference servers(vLLM) 4. Version controlsystems and observability (Git, DVC, MLFlow, W&B, KubeFlow) 5. Data analysis and curation tools(Dask, Milvus, Apache Spark, Numpy) 6. Text-to-Speech tools (Whisper, Voicebox, VALL-E (X), HuBERT/Unitspeech) 7. LLMOPs Tools, Dockers etc 8. Hands on experience with AI application libraries and frameworks (DSPy, Langgraph, langchain, llamaindex etc.) Show more Show less

We are looking for a skilled and enthusiastic Applied AI/ML Engineer to be a part of our team. As an Applied AI/ML Engineer, you will be responsible for leading the entire process of foundational model development, focusing on cutting-edge generative AI techniques. Your main objective will be to implement efficient learning methods for data and compute, specifically addressing challenges relevant to the Indian scenario. Your tasks will involve optimizing model training and inference pipelines, deploying production-ready models, ensuring scalability through distributed systems, and fine-tuning models for domain adaptation. Collaboration with various teams will be essential as you work towards building strong AI stacks and seamlessly integrating them into production pipelines. Apart from conducting research and experiments, you will be crucial in converting advanced models into operational systems that generate tangible results. Your leadership in this field will involve working closely with technical team members and subject matter experts, documenting technical processes, and maintaining well-structured codebases to encourage innovation and reproducibility. This position is perfect for proactive individuals who are passionate about spearheading significant advancements in generative AI and implementing scalable solutions for real-world impact. Your responsibilities will include: - Developing and training foundational models across different modalities - Managing the end-to-end lifecycle of foundational model development, from data curation to model deployment, through collaboration with core team members - Conducting research to enhance model accuracy and efficiency - Applying state-of-the-art AI techniques in Text/Speech and language processing - Collaborating with cross-functional teams to construct robust AI stacks and smoothly integrate them into production pipelines - Creating pipelines for debugging, CI/CD, and observability of the development process - Demonstrating project leadership and offering innovative solutions - Documenting technical processes, model architectures, and experimental outcomes, while maintaining clear and organized code repositories To be eligible for this role, you should hold a Bachelor's or Master's degree in a related field and possess 2 to 5 years of industry experience in applied AI/ML. Minimum requirements for this position include proficiency in Python programming and familiarity with 3-4 tools from the specified list below: - Foundational model libraries and frameworks (TensorFlow, PyTorch, HF Transformers, NeMo, etc) - Experience with distributed training (SLURM, Ray, Pytorch DDP, Deepspeed, NCCL, etc) - Inference servers (vLLM) - Version control systems and observability (Git, DVC, MLFlow, W&B, KubeFlow) - Data analysis and curation tools (Dask, Milvus, Apache Spark, Numpy) - Text-to-Speech tools (Whisper, Voicebox, VALL-E (X), HuBERT/Unitspeech) - LLMOPs Tools, Dockers, etc - Hands-on experience with AI application libraries and frameworks (DSPy, Langgraph, langchain, llamaindex, etc),