12 Multimodal Models Jobs

About Us: At Calfus, we are known for delivering cutting-edge AI agents and products that transform businesses in ways previously unimaginable. We empower companies to harness the full potential of AI, unlocking opportunities they never imagined possible before the AI era. Our software engineering teams are highly valued by customers, whether start-ups or established enterprises, because we consistently deliver solutions that drive revenue growth. Our ERP solution teams have successfully implemented cloud solutions and developed tools that seamlessly integrate with ERP systems, reducing manual work so teams can focus on high-impact tasks. None of this would be possible without talent like you! Our global teams thrive on collaboration, and were actively looking for skilled professionals to strengthen our in-house expertise and help us deliver exceptional AI, software engineering, and solutions using enterprise applications. As one of the fastest-growing companies in our industry, we take pride in fostering a culture of innovation where new ideas are always welcomedwithout hesitation. We are driven and expect the same dedication from our team members. Our speed, agility, and dedication set us apart, and we perform best when surrounded by high-energy, driven individuals. To continue our rapid growth and deliver an even greater impact, we invite you to apply for our open positions and become part of our journey! About the role: We are seeking a highly motivated and experienced Technical Product Manager to lead the development and management of AI-powered products that leverage cutting-edge generative AI technologies. The ideal candidate will combine deep technical understanding of AI/ML, especially in large language models (LLMs), multimodal models, or generative media, with strong product management skills. You will collaborate closely with cross-functional teams to define product strategy, roadmap, and features while ensuring alignment with business objectives and technical feasibility. A successful candidate will have a solid foundation in software development, experience leading agile teams, a strong handle on cloud-based deployments, and a fair understanding of Generative AI technologies and how they can be applied to real-world products. Position Overview: Product Delivery & Implementation Translate product vision and roadmap into detailed requirements and technical specifications. Own end-to-end implementation planning, including API design, data flow, and system integration. Work closely with engineering leads on technical designs, ensuring feasibility, scalability, and performance. Agile Leadership Lead and manage scrum ceremonies including daily stand-ups, sprint planning, retrospectives, and backlog grooming. Define and maintain the product backlog, ensuring user stories are clear, well-prioritized, and aligned with strategic goals. Act as the bridge between business stakeholders and engineering teams to ensure alignment and transparency. Deployment & Delivery Oversight Coordinate and monitor product deployments across development, staging, and production environments. Work with DevOps and QA teams to ensure timely and stable releases. Define success metrics and monitor product performance post-deployment. What Youll Do: Product Strategy: Develop and execute a comprehensive product strategy for our fintech products, aligning with overall business goals and market trends. Market Analysis: Conduct thorough market research to identify customer needs, competitive landscape, and emerging trends. Product Roadmap: Create and manage a detailed product roadmap, prioritizing features and functionalities based on business value and technical feasibility. Feature Definition: Collaborate with stakeholders to define product requirements, user stories, and acceptance criteria. Product Development: Work closely with engineering teams to ensure efficient and timely product development, providing guidance and oversight throughout the process. Product Launch: Plan and execute successful product launches, including marketing campaigns, customer education, and go-to-market strategies. Product Management: Monitor product performance post-launch, gather feedback from customers and stakeholders, and continuously iterate and improve the product. Cross-Functional Collaboration: Work effectively with teams across the organization, including engineering, design, marketing, sales, and customer success. On your first day, we&aposll expect you to have: 5+ years of experience in product management (Technical), with a good understanding on technologies and Generative AI Experience managing Agile/Scrum teams and driving sprint execution. Strong understanding of machine learning, deep learning, and especially generative AI concepts. Strong background in software development, cloud computing, and financial technologies, with the ability to understand and contribute to architectural discussions. Excellent analytical and problem-solving skills. Great communication skills, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders. Familiarity with financial regulations and compliance requirements, particularly in the areas of data security and privacy Ability to work independently and as part of a team. Benefits: At Calfus, we value our employees and offer a strong benefits package. This includes medical, Group, and parental insurance, coupled with gratuity and provident fund. Further, we support employee wellness and provide birthday leave as a valued benefit. Calfus is an Equal Opportunity Employer That means we do not discriminate against any applicant for employment, or any employee because of age, color, sex, disability, national origin, race, religion, or veteran status. All employment is decided based on qualifications, merit, and business need. Show more Show less

We are looking for a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate should have hands-on experience in developing, fine-tuning, and deploying LLMs, along with a deep understanding of the machine learning lifecycle. Your responsibilities will include developing and optimizing LLMs such as OpenAI's GPT, Anthropic's Claude, Google's Gemini, or AWS Bedrock. You will customize pre-trained models for specific use cases to ensure high performance and scalability. Additionally, you will be responsible for designing and maintaining end-to-end ML pipelines from data preprocessing to model deployment, optimizing training workflows for efficiency and accuracy. Collaboration with cross-functional teams, integration of ML solutions into production environments, experimentation with new approaches to improve model performance, and staying updated with advancements in LLMs and generative AI technologies will also be part of your role. You will collaborate with data scientists, engineers, and product managers to align ML solutions with business goals and provide mentorship to junior team members. The qualifications we are looking for include at least 5 years of professional experience in machine learning or AI development, proven expertise with LLMs and generative AI technologies, proficiency in Python (required) and/or Java (bonus), hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock, familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face, and a strong understanding of data structures, algorithms, and distributed systems. Cloud expertise in AWS, GCP, or Azure, including services relevant to ML workloads such as AWS SageMaker and Bedrock, proficiency in handling large-scale datasets and implementing data pipelines, experience with ETL tools and platforms for efficient data preprocessing, strong analytical and problem-solving skills, and the ability to debug and resolve issues quickly are also required. Preferred qualifications include experience with multi-modal models, generative AI for images, text, or other modalities, understanding of ML Ops principles and tools like MLflow and Kubeflow, familiarity with reinforcement learning and distributed training techniques and tools like Horovod or Ray, and an advanced degree (Master's or Ph.D) in Computer Science, Machine Learning, or a related field.,

As an NLP Engineer at Tiger Analytics, you will have the opportunity to work on cutting-edge AI and analytics projects to help Fortune 1000 companies overcome their toughest challenges. You will be part of a global team of technologists and consultants dedicated to empowering businesses to achieve real outcomes and value at scale. Your role will involve collaborating with experienced team members on internal product development and client-focused projects, with a focus on the pharma domain. You will play a key role in designing, developing, and deploying GenAI solutions, with a particular emphasis on addressing challenges like hallucinations, bias, and latency. Your day-to-day responsibilities will include supporting the full lifecycle of AI project delivery, fine-tuning Large Language Models (LLMs) for specific business needs, and developing scalable pipelines for AI model deployment. You will also have the opportunity to collaborate with internal teams and external stakeholders, particularly in the pharma space, to understand business requirements and contribute to the development of tailored AI-powered systems. Additionally, you will actively participate in a collaborative environment, sharing ideas and working as part of a dynamic team of data scientists and AI engineers. To be successful in this role, you should have 7-9 years of experience in NLP, AI/ML, or data science, with a proven track record of delivering production-grade NLP & GenAI solutions. You should have deep expertise in LLMs, transformer architectures, and fine-tuning techniques, as well as strong knowledge of NLP pipelines, text preprocessing, embeddings, and named entity recognition. Experience with Agentic AI systems, LLM observability tools, and AI safety guardrails is also essential. Proficiency in Python and backend development, familiarity with MLOps and cloud platforms, and prior experience in regulated industries like life sciences or pharma are all advantageous. A problem-solving mindset, the ability to work independently, drive innovation, and mentor junior engineers are key qualities we are looking for in candidates. The compensation package for this role will be commensurate with your expertise and experience, and you will also have access to additional benefits such as health insurance, a virtual wellness platform, and knowledge communities.,

As an AI/ML Consultant specializing in Generative AI and Machine Learning, you will leverage your 8+ years of experience to lead and deliver AI initiatives in the Healthcare, BFSI, and Manufacturing sectors. Your role will involve collaborating with stakeholders to develop scalable AI solutions that integrate Generative AI techniques like LLMs and transformers with traditional ML approaches such as time series analysis, classification, and deep learning. Your core responsibilities will include: AI/ML Strategy & Delivery: - Leading end-to-end AI/ML projects, from concept to implementation. - Working closely with stakeholders to transform business requirements into effective AI solutions. - Applying a combination of Generative AI and traditional ML methods to address diverse industry challenges. Technical & Platform Expertise: - Designing and implementing GenAI solutions using technologies like LLMs, agentic AI, and LangChain. - Hands-on experience with NLP, RAG, LoRA/PEFT, and prompt engineering. - Proficiency in Python programming and familiarity with TensorFlow, PyTorch, and HuggingFace. - Expertise in working with vector databases such as FAISS, Chroma, and Pinecone. - Implementing MLOps best practices, including CI/CD and ML model lifecycle management with tools like MLflow. Integration & Innovation: - Developing AI-powered applications using frameworks like Streamlit and FastAPI. - Deploying models on cloud platforms like AWS, Azure, and GCP, as well as GPU/TPU accelerators. - Collaborating with engineering and product teams to integrate AI solutions into enterprise systems. Qualifications for this role include: - 8+ years of experience in AI/ML, with at least 2-3 years in client-facing or leadership positions. - Demonstrated expertise in leading complex AI programs and providing guidance to senior executives. - Bachelor's or Master's degree in Computer Science, Data Science, AI, or related fields. - Industry certifications in AWS, Azure, GCP, or Databricks would be beneficial. - Knowledge of regulated industries such as Healthcare, Pharma, and BFSI is preferred. In addition to your technical skills, strong communication abilities will be essential for effectively conveying complex technical concepts to non-technical audiences. Stay informed about the latest AI trends, including multimodal models and ethical AI practices, to drive innovation and maintain industry relevance.,

Nanonets is revolutionizing the way companies streamline document-heavy and unstructured data workflows through AI Agents. Our client portfolio includes industry giants such as Adobe, Schneider Electric, and Boston Scientific. With strong support from renowned investors, we are experiencing rapid growth and are seeking exceptional engineers to join our purpose-driven team. As a part of our team, you will play a crucial role in developing and implementing cutting-edge generalised deep learning architectures that are capable of addressing intricate business challenges. Your primary focus will involve creating solutions for converting unstructured data into a structured format without the need for manual feature or model adjustments. We expect you to design state-of-the-art models that are globally recognized for their effectiveness in solving these complex problems. Additionally, you will be responsible for continuously exploring and integrating the latest advancements in the field to enhance these architectures. Ideal candidates should possess: - 5-8 years of hands-on experience in Deep Learning - Solid foundational understanding of deep learning concepts and architectures, including LLMs and VLMs - Demonstrated expertise in at least one specialized area of deep learning such as NLP, computer vision, or multimodal models - Proven track record of building and implementing production-grade Deep Learning systems at scale - Familiarity with various large language models like GPT, LLaMA, and Claude, along with their practical applications - Strong software engineering skills encompassing version control, CI/CD practices, and code quality assurance - Ability to quickly adapt and utilize new technologies and methodologies effectively Noteworthy projects completed by our Senior DL Engineers: - Deployment of large-scale multi-modal architectures proficient in comprehending both text and images with high accuracy - Development of an auto-ML platform capable of autonomously selecting the optimal architecture and fine-tuning method based on data type and volume - Creation of world-class models for processing diverse documents like invoices, receipts, passports, driving licenses, etc. - Implementation of robust modelling techniques for extracting hierarchical information from documents with tree-like structures - Extraction of complex tables with intricate formats such as wrapped tables, multi-field columns, cells spanning multiple columns, and tables in distorted images - Facilitation of few-shot learning through cutting-edge finetuning techniques that are at the forefront of the industry Join us at Nanonets and be a part of a dynamic team that is shaping the future of AI-driven document automation solutions.,

You should have a strong hold on the Software Development Life Cycle (SDLC), Python Scripting, and AI packages. Your conceptual knowledge should include GenAI techniques such as Prompt engineering (Template, Curation, modification) and various foundation models related to text, image, video, and other data. Experience in DNN module training & Integration, CNN, Transformer/RNN is essential. You should also possess GenAI knowledge in LLM, Multimodal Models (Stable diffusion/Autoregression/Diffusion Transformer) to utilize World Foundation model and peripheral development effectively. Additionally, familiarity with Finetuning (Transfer learning) techniques for Multimodal Foundation models and Multi-modal Data pipeline (Cleaning, augmentation, embedding creation) is required. Data pruning/Curation and labeling with respect to AI training and validation is also part of the responsibilities. Knowledge of AD domain including domain stack components, Features, Sensor configuration, Format, and types of Annotations required for various components in the stack for development/testing, Validation is necessary. Proficiency in Python, GENAI, DNN, CNN, LLM is a must. Experience in Automotive, ADAS, and AD Domain will be beneficial for this role.,

You will be part of our team as a Researcher at Infosys Applied AI research team. Your role will involve designing, developing, and training transformer-based models for multiple-modality to support various AI-powered applications. You will experiment with different architectures, training techniques, and optimization methods to enhance the models" understanding and generative capabilities. Additionally, you will be responsible for innovating robust and scalable architectures to meet future requirements and troubleshooting model issues to ensure their robustness and adaptability. To qualify for this position, you should have at least 8 years of experience and hold a Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related fields (Ph.D. preferred). You must have proven experience in training models, particularly text and multi-modal models, along with a strong knowledge of transformer architectures and their underlying principles. Experience with model pre-training, fine-tuning, and distributed training is essential. Moreover, having one or more scientific publication submissions for conferences, journals, or public repositories (e.g., ICML, ICLR, NeurIPS) will be advantageous. By joining our team, you will have the opportunity to work on cutting-edge projects that are at the forefront of artificial intelligence. You will play a crucial role in contributing to groundbreaking advancements in NLP and AI while working in an innovative and dynamic environment. We offer competitive compensation and benefits package, along with a flexible work environment. While Bangalore is preferred, we are open to considering candidates from multiple locations in India.,

As an ideal candidate, you should have a strong grasp of the Software Development Life Cycle (SDLC), Python Scripting, and Artificial Intelligence (AI) packages. Your conceptual knowledge should extend to General Artificial Intelligence (GenAI) techniques, including Prompt engineering such as Template, Curation, and modification. You should be well-versed in various foundation models related to text, image, video, and other data. Experience in training and integrating Deep Neural Network (DNN) modules, Convolutional Neural Network (CNN), and Transformer/Recurrent Neural Network (RNN) is essential for this role. Additionally, you should possess GenAI knowledge concerning Large Language Models (LLM) and Multimodal Models like Stable diffusion, Autoregression, and Diffusion Transformer for utilizing World Foundation models and peripheral development. Your expertise should also include fine-tuning (Transfer learning) techniques for Multimodal Foundation models, as well as managing Multi-modal Data pipelines involving tasks like cleaning, augmentation, and creating embeddings. You should be familiar with Data pruning/Curation and labeling in the context of AI training and validation. Furthermore, a good understanding of the Autonomous Driving (AD) domain is required, encompassing knowledge of domain stack components, features, sensor configuration, and the format and types of annotations necessary for various components in the stack for development and testing. Your comprehensive skill set in these areas will be crucial for excelling in this position.,

As a Senior AI Engineer at Teradata, you will play a vital role in shaping the future of enterprise AI by designing and deploying advanced AI agents that integrate deeply with business operations. You will be part of a high-caliber team of AI researchers, engineers, and data scientists, working on cutting-edge AI solutions for large-scale enterprise environments. Your responsibilities will include architecting and implementing Agentic AI systems, building AI observability pipelines, designing data platform components, and integrating LLMs and multi-modal models into robust AI agents. You will collaborate closely with product, research, and MLOps teams to ensure smooth integration between AI agents and user-facing applications. Your role will involve implementing safeguards, feedback loops, and evaluation metrics to ensure AI safety, reliability, and compliance. Additionally, you will stay current with AI research, especially in the areas of reasoning, planning, and autonomous systems, and contribute to the development of reliable and deterministic AI systems. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. A genuine excitement for AI and large language models (LLMs) is advantageous, along with 5+ years of experience in software architecture, backend systems, or AI infrastructure. Strong engineering skills in Python, Java, or Golang, along with hands-on experience in Machine learning & deep learning frameworks like TensorFlow, PyTorch, and Scikit-learn, are essential. Your background should include experience with LLMs, transformers, AI observability tools, and modern data platform architecture. Familiarity with distributed systems, microservices, cloud platforms, and containerized environments like Docker and Kubernetes is preferred. Bonus points for research experience or contributions to open-source agentic frameworks. Teradata offers a people-first culture, flexible work model, focus on well-being, and commitment to Diversity, Equity, and Inclusion, making it an ideal workplace for passionate AI professionals.,

Job Description: Strategic Technology Group is a core team within Infosys supported by Power Programmers who are tech polyglots Our team of Power Programmers works on complex projects and builds solutions to solve some of the world s most challenging business problems Introduction We are looking for a passionate and talented Researcher to join Infosys Applied AI research team As an Researcher you will work on architecting building refining and optimizing state of the art Models that drive cutting edge multi modal multi domain understanding and generation capabilities If you have experience building LLM SLM Multimodal models we would love to hear from you Why Join Us Work with an innovative team on cutting edge projects that are pushing the boundaries of artificial intelligence Opportunity to grow professionally and contribute to groundbreaking advancements in NLP and AI Competitive compensation and benefits package Bangalore preferred Flexible work environment with remote work options available Key Responsibilities: Design develop and train transformer based models for multiple modality to support a variety of AI powered applications Experiment with various architectures training techniques and optimization methods to improve the model s understanding and generative capabilities Innovate robust and scalable architectures to accommodate the future requirements Troubleshoot and debug model issues ensuring the models remain robust and adaptable Technical Requirements: We are looking for a passionate and talented Researcher to join Infosys Applied AI research team As an Researcher you will work on architecting building refining and optimizing state of the art Models that drive cutting edge multi modal multi domain understanding and generation capabilities If you have experience building LLM SLM Multimodal models we would love to hear from you Additional Responsibilities: Master s degree or PhD in Computer Science Artificial Intelligence Machine Learning or related fields Ph D preferred Proven experience in training models both text and multi modal models Strong knowledge of transformer architectures and their underlying principles Experience with model pre training finetuning and distributed training One or more scientific publication submissions for conferences journals or public repositories e g ICML ICLR NeurIPS Preferred Skills: Technology->Artificial Intelligence->Artificial Intelligence - ALL

Role & responsibilities Architect and implement AI/ML solutions tailored to client-specific business problems using Gen AI (e.g., LLMs like GPT, Gemini, Mistral) and traditional ML models (e.g., scikit-learn, XGBoost). Collaborate with client stakeholders to understand requirements, define problem statements, and translate them into scalable AI/ML solutions. Present demos and proof-of-concepts (POCs) to clients, showcasing the value of AI/ML in real-world scenarios Mentor and guide a cross-functional team of data scientists, ML engineers, and developers Drive best practices in model development, deployment, and monitoring Stay abreast of the latest advancements in Gen AI and ML, and evaluate their applicability to client use cases Contribute to internal knowledge bases and reusable solution accelerators Preferred candidate profile Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with Gen AI platforms and LLMs (e.g., OpenAI, Gemini, LLaMA, Mistral). Proven track record of deploying ML models in production environments (cloud/on-prem). Experience with API development, data pipelines, and dashboarding tools like Streamlit. Familiarity with DevOps and MLOps practices for model lifecycle management. Excellent communication and stakeholder management skills. Tools: LLM, SLM, Vector DB, Graph DB, Airflow, MLFlow, MLOps tools, NLP, KG, ML models (Regression, Clustering, Classification etc), LangChain, LangGraph, AutoGen

The Oracle Global Business Unit (GBU) Generative AI team is responsible for leading Generative AI and Agent needs of business applications serving variety of markets including Finance, Hospitality, Construction and Engineering, Energy & Water etc. Our goal is to enable customers to apply AI to solve their business problems with Oracle's assistance and expertise in Generative AI. In this role, you will have an opportunity to work with teams of applied scientists and engineers to deliver high quality generative ai and agent features that delights our customers with the confidence that their data are safe and protected. Your Opportunity We are seeking a Principal Applied Scientist (IC4) to spearhead Generative AI and Agent use cases that support GBU business applications as well as GBU consulting. As an applied scientist, you will be responsible for driving the development and implementation of cutting-edge technologies.We are building a core talented team specialized in Generative AI. We are looking for candidates who are passionate about building state-of-the-art technologies to solve real-world problems and have a solid technical background in deep learning, especially natural language processing (NLP) and multimodal models, to join this team. You will collaborate with a team of world-class scientists, engineers and product managers.We're looking for a person who will bring a passion for innovative products, strong collaboration skills and the ability to work closely with both development and consulting teams. You'll be a Generative AI expert who is hands-on as well as be adept at evangelizing and influencing multiple stakeholders without direct authority on best practices and to get things done efficiently. Most importantly - we believe in a people-first approach. Our team consists of people from a wide variety of backgrounds, with different professional and life experiences, who support each other to build things the right way and enjoy ourselves while doing it. What we offer Being part of one of the most visionary and mission-driven organizations in Oracle, cooperating with talented peers with diverse backgrounds worldwide. High visibility to senior leadership, as well as technical leaders and partners. Opportunity to build state-of-the-art technologies in large language models and generative AI at scale. Close partnership with product managers and software engineers to deploy Generative AI features into products in various business-critical scenarios. Building performance evaluations of Generative AI systems for continuous improvement of alignment with stakeholders growing expectations. What You'll Do Develop, implement, and optimize large language models and generative AI technologies, including training/finetuning and computation optimizations. Collaborate with software engineers to deploy LLM / Generative AI models and Agents into production environments. Stay up-to-date with the latest advancements in the field of generative AI. Collaborate with cross-functional teams to drive the development and adoption of LLM and generative AI solutions across various organizations in the company. Work directly with key customers and accompany them on their AI journey - understanding their requirements, help them envision and design the right solutions and work together with their engineering and data science team to remove blockers and translate the feedback into actionable items for individual service owners. Design and build solutions and help GBU development teams reach successful pilots, PoCs and feature releases with our AI/Gen AI and DS technologies. Bring back learnings from these engagements to standardize Generative AI and Agent implementations for efficiency, scale and ease of maintenance. Support GBU consulting with re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Being enthusiastic, self-motivated, and a great collaborator. Lead patent filings and author papers to show innovative enterprise grade developments. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications: PhD, MS in computer science, engineering, mathematics or a field related to deep learning. Strong knowledge of ML fundamentals - supervised vs unsupervised modeling, time series, highly unbalanced and noisy data sets, complex feature engineering, recommendation systems, using and optimizing gradient boosting models, NLP, deep learning on all kinds of unstructured data. 5+ (for Senior), 7+ (for Principal), 10+ (for Sr Principal) years of work experience including a minimum of 2-year experience in developing large-scale ML solutions, and in particular deep learning solutions in the NLP field. Proficiency with deep learning frameworks (such as PyTorch or TensorFlow) and deep learning architectures (especially Transformers). Hands-on experience with distributed training of large language models. Strong development experience of deep learning modeling in Python. Familiarity with the latest advancements in LLM and generative AI technologies. Familiarity with engineering best practices, including shared codebase, version control, containerization, etc. Passionate about being a builder and working with talented peers to solve hard problems at scale. Good communication skills to convey technical concepts in straightforward terms with product managers and various stakeholders. Preferred Skills Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories Industrial experience in system design, software development, and production deployment Excel in transforming ambiguous requirements into actionable plans with deep learning techniques for problem-solving. First-hand experience with deep reinforcement learning First-hand experience with the latest technologies in LLM and generative AI such as parameter-efficient finetuning and instruction finetuning is a plus Familiarity with the latest advancements in computer vision and multimodal models is a plus Top-tier performance in prestigious deep learning leaderboards or large model-related competitions is a plus. Career Level - IC5 Drives and plans implementation of company policy for achieving business goals. Defines the bar for science practices, and helps teams achieve those goals. Identifies and mitigates risks across full set of systems, particularly at the intersection of business and engineering. Innovate AI and ML powered solutions (rich APIs, ML models and end to end services) with strategic ISVs and customers. Develop deep product intuition to influence future product roadmaps and drive decision making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward looking research both internal and with academic institutions globally. Hires and mentors across the org. Perform an active role in team planning, review and retrospective events. Ensures experiments are ready for hand-off to Software Developers ship into production. May perform other duties as assigned.