6 Stable Diffusion Jobs

Job Overview: We are looking for a GenAI Leader with 12+ years of experience and a strong background in pharma/life sciences to join our team. As a key leader, you will drive innovation in the pharma commercial and clinical space by designing cutting-edge AI solutions, leading high-performing teams, and delivering impactful results. If you have a proven track record in Generative AI, hands-on experience with models like GPT, DALL-E, and Stable Diffusion, and a passion for mentoring and thought leadership, we want to hear from you! Must have skills & competencies Enhance the go-to-market strategy by designing new and relevant solution frameworks to accelerate our clients journeys for impacting patient outcomes. Pitch for these opportunities and craft winning proposals to grow the Data Science Practice. Build and lead a team of data scientists and analysts, fostering a collaborative and innovative environment. Oversee the design and delivery of the models, ensuring projects are completed on time and meet business objectives. Engaging in consultative selling with clients to grow/deliver business. Develop and operationalize scalable processes to deliver on large & complex client engagements. Proven experience in building and productizing GenAI app at an enterprise level Ensure profitable delivery and great customer experience – design the end-to-end solution, put together the right team and help them deliver as per established processes. Build an A team – hire the required skills sets and nurture them in a supporting environment to develop strong delivery leaders for the Data Science Practice. Train and mentor staff and establish best practices and ways of working to enhance data science capabilities at Axtria. Operationalize an eco-system for continuous learning & development. Write white papers, collaborate with academia and participate in relevant speaker opportunities to continuously upgrade learning & establish Axtria’s thought leadership in this space. Research, develop, evaluate and optimize newly emerging algorithms and technologies for relevant use cases in pharma commercial & clinical space. Extensive hands-on experience with Python, R, or Julia, focusing on data science and generative AI frameworks. Expertise in working with generative models such as GPT, DALL-E, Stable Diffusion, Codex, and MidJourney for various applications. Proficiency in fine-tuning and deploying generative models using libraries like Hugging Face Transformers, Diffusers, or PyTorch Lightning. Strong understanding of generative techniques, including GANs, VAEs, diffusion models, and autoregressive models. Experience in prompt engineering, zero-shot, and few-shot learning for optimizing generative AI outputs across different use cases. Expertise in managing generative AI data pipelines, including preprocessing large-scale multimodal datasets for text, image, or code generation. Experience in leveraging APIs and SDKs for generative AI services from OpenAI, Anthropic, Cohere, and Google AI. Expertise in defining generative AI strategies, aligning them with business objectives, and implementing solutions for scalable deployment. Knowledge of real-world applications of generative AI, such as text generation, code generation, image generation, chatbots, and content creation. Awareness of ethical considerations in generative AI, including bias mitigation, data privacy, and safe deployment practices. Good to have skills & competencies Proven ability to collaborate with cross-functional teams, including product managers, data scientists, and DevOps engineers, to deliver end-to-end generative AI solutions. Proven experience in leading teams focused on generative AI projects, mentoring ML engineers, and driving innovation in AI applications. Possessing robust analytical skills to address and model intricate business needs is highly advantageous, especially for those with a background in life sciences or pharmaceuticals. Eligibility Criteria Masters/PhD in CSE/IT from Tier 1 institute Minimum 12+ years of relevant experience in building software applications in data and analytics field. We will provide– (Employee Value Proposition) Offer an inclusive environment that encourages diverse perspectives and ideas Delivering challenging and unique opportunities to contribute to the success of a transforming organization Opportunity to work on technical challenges that may impact on geographies Vast opportunities for self-development: online Axtria Institute, knowledge sharing opportunities globally, learning opportunities through external certifications Sponsored Tech Talks & Hackathons Possibility of relocating to any Axtria office for short and long-term projects Benefit package: -Health benefits -Retirement benefits -Paid time off -Flexible Benefits -Hybrid /FT Office/Remote Axtria is an equal-opportunity employer that values diversity and inclusiveness in the workplace. Who we are Axtria 14 years journey Axtria, Great Place to Work Life at Axtria Axtria Diversity

Role & responsibilities Key Skills required : Generative AI, Multi Modal AI Creative AI solutions and workflows across all creative content types including Copy/Text, Imagery, Key Visuals, Characters, Avatars, Audio, Speech and Video AI Creative AI Automation workflows with content creation and content editing at scale, using AI services and AI APIs Experience with multiple Multi Modal AI Foundation Models LLM, LLM App Dev AI Agents, Agentic AI Workflows Responsibilities : Design and build web apps and solutions that leverage Creative AI Services, Multi Modal AI models, and Generative AI workflows Leverage Multi modal AI capabilities supporting all content types and modalities, including text, imagery, audio, speech and video Build creative automation workflows that help produce creative concepts, creative production deliverables, and integrated creative outputs, leveraging AI and Gen-AI models Integrate AI Image Gen Models and AI Image Editing models from key technology partners Integrate Text / Copy Gen Models for key LLM providers Integrate Speech / Audio Gen and Editing models for use cases such as transcription, translation, and AI generated audio narration Integrate AI enabled Video Gen and Video Editing models Fine-Tune Multi Modal AI models for brand specific usage and branded content generation Constantly Research and explore emerging trends and techniques in the field of generative AI and LLMs to stay at the forefront of innovation. Drive product development and delivery within tight timelines Collaborate with full-stack developers, engineers, and quality engineers, to develop and integrate solutions into existing enterprise products. Collaborate with technology leaders and cross-functional teams to develop and validate client requirements and rapidly translate them into working solutions. Develop, implement and optimize scalable AI-enabled products Integrate Gen-AI and Multi Modal AI solutions into Cloud Platforms, Cloud Native Apps, and custom Web Apps Execute implementation across all layers of the application stack including front-end, back-end, APIs, data and AI services Build enterprise products and full-stack applications on the MERN + Python stack, with a clear separation of concerns across layers Skills and Competencies: Deep Hands-on Experience in Multi modal AI models and tools. Hands-on Experience in API integration with AI services Multi Modal AI – competencies : Hands-on Experience with intelligent document processing and document indexing + document content extraction and querying, using multi modal AI Models Hands-on Experience with using Multi modal AI models and solutions for Imagery and Visual Creative – including text-to-image, image-to-image, image composition, image variations, etc. Hands-on Experience with popular AI Image Composition and Editing models from providers such as Adobe Firefly, Getty Images, ShutterStock, Flux and Flux Pro, and Stable Diffusion, and the ability to integrate them programmatically over API calls and workflows Hands-on Experience with Computer Vision and Image Processing using Multi-modal AI – for use cases such as object detection, automated captioning, automated masking, and image segmentation – again all done programmatically over API calls and Workflows Hands-on Experience with using Multi modal AI for Speech – including Text to Speech, Speech to Text, and use of Pre-built vs. Custom Voices Hands-on Experience with building Voice-enabled and Voice-activated experiences, using Speech AI and Voice AI solutions Hands-on Experience with AI Character and AI Avatar development, using a variety of different tools and platforms Fine-Tuning Creative AI Content models for Custom Styles, Custom Characters, and Custom Brand specific imagery Fine-Tuning Speech Models for Custom Voices Good understanding of advanced fine-tuning techniques such as LoRA Ability to execute and run fine-tuning workflows, end-to-end, in particular for Image Gen and Image Editing models Hands-on Experience with leveraging APIs to orchestrate across Multi Modal AI models Hands-on Experience with building workflows that orchestrate across Multi Modal AI models Good Experience with using AI Assistants to drive natural language interactions and orchestration with Multi Modal AI models Good Experience with use of AI Agents and Agentic AI workflows to drive dynamic orchestration across Multi Modal AI services and models Programming Skills : Good Expertise in MERN stack (JavaScript) including client-side and server-side JavaScript Good Expertise in Python based development, including Python App Dev for Multi Modal AI Integration Well-rounded in both programming languages Strong experience in client-side JavaScript Apps and building Static Web Apps + Dynamic Web Apps both in JavaScript Hands-on Experience in front-end and back-end development Minimum 2+ years hands-on experience in working with Full-Stack MERN apps, using both client-side and server-side JavaScript Minimum 2 years hands-on experience in Python development Minimum 2 years hands-on experience in working with LLMs and LLM models, using Python LLM Dev Skills : Solid Hands-on Experience with building end-to-end RAG pipelines and custom AI indexing solutions to ground LLMs and enhance LLM output Good Experience with building AI and LLM enabled Workflows Hands-on Experience integrating LLMs with external tools such as Web Search Ability to leverage advanced concepts such as tool calling and function calling, with LLM models Hands-on Experience with Conversational AI solutions and chat-driven experiences Experience with multiple LLMs and models – primarily GPT-4o, GPT o1, and o3 mini, and preferably also Gemini, Claude Sonnet, etc. Experience and Expertise in Cloud Gen-AI platforms, services, and APIs, primarily Azure OpenAI, and perferably also AWS Bedrock , and/or GCP Vertex AI . Hands-on Experience with Assistants and the use of Assistants in orchestrating with LLMs Hands-on Experience working with AI Agents and Agent Services . Nice-to-Have capabilities (Not essential) : Hands-on Experience with building Agentic AI workflows that enable iterative improvement of output Hands-on experience with both Single-Agent and Multi-Agent Orchestration solutions and frameworks Hands-on experience with different Agent communication and chaining patterns Ability to leverage LLMs for Reasoning and Planning workflows, that enable higher order “goals” and automated orchestration across multiple apps and tools Ability to leverage Graph Databases and “Knowledge Graphs” as an alternate method / replacement of Vector Databases, for enabling more relevant semantic querying and outputs via LLM models. Good Background with Machine Learning solutions Good foundational understanding of Transformer Models Good foundational understanding of Diffusion Models Some Experience with custom ML model development and deployment is desirable. Proficiency in deep learning frameworks such as PyTorch, or Keras. Experience with Cloud ML Platforms such as Azure ML Service, AWS Sage maker, and NVidia AI Foundry.

Proven experience in video editing and content creation. Proficiency with AI tools for face and audio generation. create visually appealing and informative digital courses. Strong command of Adobe Premiere Pro, After Effects, and similar software. Job/soft skill training Performance bonus

Location: Gurugram (Work From Office) Job Type: Full-Time Job Description: As a Senior Machine Learning Engineer , you will be responsible for designing, developing, and deploying cutting-edge models for end-to-end content generation , including AI-driven image/video generation, lipsyncing, and multimodal AI systems . You will work on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. Responsibilities: Research & Develop : Design and implement state-of-the-art generative models , including Diffusion Models, 3D VAEs and GANs for AI-powered media synthesis . End-to-End Content Generation : Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Speech & Video Synchronization : Develop advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Real-Time AI Systems : Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques . Scaling & Production Deployment : Work closely with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) . Collaboration & Research : Stay ahead of the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality. Experimentation & Validation : Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency , and refine model architectures. Code Quality & Best Practices : Participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development . Qualifications: Bachelor's or Masters degree in Computer Science, Machine Learning, or a related field. 3+ years of experience working with deep generative models , including Diffusion Models, 3D VAEs, GANs and autoregressive models . Strong proficiency in Python and deep learning frameworks such as PyTorch. Expertise in multi-modal AI, text-to-image, and image-to-video generation , audio to lipsync Strong understanding of machine learning principles and statistical methods. Good to have experience in real-time inference optimization, cloud deployment, and distributed training . Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training . Preferred Qualifications: Experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V). Background in text-to-video generation, lipsync generation and real-time synthetic media applications . Experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation) . Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis .

Experience in ComfyUI (node-based AI workflow builder) — ability to build, modify, and optimize custom pipelines.Runway, Stable Diffusion, Midjourney, DALLE, Leonardo.ai, and other generative platforms.Video generation experience ( VFX).

We are looking for a GenAI Leader with 12+ years of experience and a strong background in pharma/life sciences to join our team. As a key leader, you will drive innovation in the pharma commercial and clinical space by designing cutting-edge AI solutions, leading high-performing teams, and delivering impactful results. If you have a proven track record in Generative AI, hands-on experience with models like GPT, DALL-E, and Stable Diffusion, and a passion for mentoring and thought leadership, we want to hear from you! Must have skills & competencies Enhance the go-to-market strategy by designing new and relevant solution frameworks to accelerate our clients journeys for impacting patient outcomes. Pitch for these opportunities and craft winning proposals to grow the Data Science Practice. Build and lead a team of data scientists and analysts, fostering a collaborative and innovative environment. Oversee the design and delivery of the models, ensuring projects are completed on time and meet business objectives. Engaging in consultative selling with clients to grow/deliver business. Develop and operationalize scalable processes to deliver on large & complex client engagements. Proven experience in building and productizing GenAI app at an enterprise level Ensure profitable delivery and great customer experience design the end-to-end solution, put together the right team and help them deliver as per established processes. Build an A team hire the required skills sets and nurture them in a supporting environment to develop strong delivery leaders for the Data Science Practice. Train and mentor staff and establish best practices and ways of working to enhance data science capabilities at Axtria. Operationalize an eco-system for continuous learning & development. Write white papers, collaborate with academia and participate in relevant speaker opportunities to continuously upgrade learning & establish Axtria's thought leadership in this space. Research, develop, evaluate and optimize newly emerging algorithms and technologies for relevant use cases in pharma commercial & clinical space. Extensive hands-on experience with Python, R, or Julia, focusing on data science and generative AI frameworks. Expertise in working with generative models such as GPT, DALL-E, Stable Diffusion, Codex, and MidJourney for various applications. Proficiency in fine-tuning and deploying generative models using libraries like Hugging Face Transformers, Diffusers, or PyTorch Lightning. Strong understanding of generative techniques, including GANs, VAEs, diffusion models, and autoregressive models. Experience in prompt engineering, zero-shot, and few-shot learning for optimizing generative AI outputs across different use cases. Expertise in managing generative AI data pipelines, including preprocessing large-scale multimodal datasets for text, image, or code generation. Experience in leveraging APIs and SDKs for generative AI services from OpenAI, Anthropic, Cohere, and Google AI. Expertise in defining generative AI strategies, aligning them with business objectives, and implementing solutions for scalable deployment. Knowledge of real-world applications of generative AI, such as text generation, code generation, image generation, chatbots, and content creation. Awareness of ethical considerations in generative AI, including bias mitigation, data privacy, and safe deployment practices. Good to have skills & competencies Proven ability to collaborate with cross-functional teams, including product managers, data scientists, and DevOps engineers, to deliver end-to-end generative AI solutions. Proven experience in leading teams focused on generative AI projects, mentoring ML engineers, and driving innovation in AI applications. Possessing robust analytical skills to address and model intricate business needs is highly advantageous, especially for those with a background in life sciences or pharmaceuticals.