5480 Deep Learning Jobs - Page 14

Job Summary: We're seeking a skilled Computer Vision Engineer to develop and deploy AI-powered computer vision models using Convolutional Neural Networks (CNNs) and unsupervised learning techniques. The ideal candidate will have expertise in designing and training camera-based AI models for various applications. Roles & Responsibilities Spearhead the development of high-performance, real-time computer vision algorithms for autonomous gun turret platforms, with emphasis on aerial threat detection, multi-object tracking, and dynamic classification of drones. Architect and fine-tune deep learning models optimized for deployment on edge computing platforms with stringent resource constraints, ensuring minimal latency and maximal inference accuracy. Collaborate cross-functionally with electrical and embedded systems engineers to seamlessly integrate vision modules into custom hardware architectures, including FPGA and SoC-based systems. Design and execute rigorous validation protocols using synthetic and real-world datasets to benchmark algorithmic performance under diverse environmental and operational conditions. Provide technical leadership and mentorship to junior engineers, fostering domain expertise in AI-driven perception systems and scalable machine learning pipelines. Drive the maturation of prototype vision systems into production-ready, defense-grade solutions, supporting modular adaptations for varied weapon platforms, engagement distances, and mission profiles. Design, develop, and deploy computer vision models using CNNs and unsupervised learning techniques. Work with camera-based datasets to train and fine-tune models for specific applications. Implement and optimize algorithms for object detection, tracking, and classification. Technical Competency: Programming Languages - Python, C++, ML Frameworks - TensorFlow, PyTorch Embedded Systems - Integration & optimization Sensor Technologies - Cameras, LIDAR, RADAR Real-Time Systems - Algorithm deployment & tuning Hardware Integration - Embedded vision systems Skillsets: Strong analytical and problem-solving abilities in computer vision and robotics. Excellent communication and collaboration skills for cross-functional teamwork. Leadership and mentoring capabilities to guide junior engineers. Ability to work in high-stakes, mission-critical environments with attention to detail. Knowledge of computer vision libraries (e.g., OpenCV, YOLO). Functional Expertise: Machine Learning & Computer Vision: End-to-end development and deployment of ML-based vision systems. Robotics: Experience with autonomous systems and sensor fusion. System Integration: Hardware-software co-design and embedded deployment. Defense Applications: Understanding of military-grade system requirements and operational constraints. What We Offer: Competitive salary and benefits package. Opportunities for professional growth and development. Collaborative and dynamic work environment. Working on National Security Projects. If you're passionate about computer vision and AI, we'd love to hear from you! Role & responsibilities Preferred candidate profile

Design and develop intelligent systems such as predictive analytics, recommendation engines,chatbots Collect, clean, and prepare datasets for training AI/ML models Build, test, and deploy machine learning models to solve business problems Required Candidate profile Candidate must be from Raipur , Chhattisgarh.

Job Title: AI Lead Engineer Job Locations: Hyderabad, Indore, Ahmedabad (India) Offices in: Austin (USA), Singapore, Hyderabad, Indore, Ahmedabad (India) About the Role We are seeking an experienced AI Lead Engineer to lead innovation in AI-driven solutions with global impact. This role demands strong expertise in Python and Java, deep experience in Retrieval-Augmented Generation (RAG)-based chatbot development, and proficiency in deploying AI applications on AWS. As the AI Lead Engineer, you will own the end-to-end development lifecycle from architecture to deployment while mentoring the team, ensuring technical excellence, and delivering scalable AI products. What You Will Do Lead the design and development of AI-driven applications, focusing on RAG-based chatbot solutions Architect robust solutions in Python and Java ensuring scalability, reliability, and maintainability Deploy, manage, and scale AI applications on AWS using EC2, Lambda, SageMaker, DynamoDB, CloudWatch, and API Gateway Collaborate with cross-functional teams to define requirements, project scopes, and delivery timelines Mentor and guide team members on AI methodologies, best coding practices, and cloud deployments Conduct thorough testing, debugging, performance tuning, and documentation to ensure high-quality delivery Stay updated on emerging AI technologies and recommend innovative solutions for business problems What You Will Bring Education: Bachelors or Masters degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or related fields Experience: 5+ years of professional experience in AI/Machine Learning engineering Proven hands-on experience building RAG-based chatbots or generative AI applications Strong programming skills in Python and Java Proficiency in AWS (EC2, Lambda, SageMaker, DynamoDB, CloudWatch, API Gateway) Solid understanding of NLP, vector databases, embedding models, and large language model integrations Experience leading projects or teams and ensuring technical deliverables meet quality standards Primary Skills #Python #Java #RetrievalAugmentedGeneration #Chatbots #MachineLearning #DeepLearning #NLP #VectorDatabases #EmbeddingModels #AWS #EC2 #Lambda #SageMaker #DynamoDB #CloudWatch #APIGateway #Leadership #SolutionArchitecture How to Apply Send your updated resume to: navaneetha@suzva.com Include the following details in your email: Total Experience Relevant Experience in AI/RAG-based Chatbots Current CTC Expected CTC Current Location Preferred Job Location (Hyderabad, Indore, Ahmedabad) Notice Period / Availability

We are seeking a highly experienced and innovative First Responder AI Expert with 3-8 years of experience to lead the development of AI agents designed for instant, context-aware responses. This role is a blend of AI engineering, natural language processing (NLP), and deep domain knowledge of business operations. The ideal candidate will be responsible for creating, deploying, and optimizing AI agents that act as a "first responder" to various queries and eventsfrom a customer's support request to an internal employee's question about HR policies or a sales team's need for real-time data. You will be instrumental in automating support, knowledge access, and operational workflows across the organization. Key Responsibilities: End-to-End Agent Development: Design, develop, and deploy conversational and autonomous AI agents that can triage, answer, and resolve user requests in real-time. Leverage and fine-tune large language models (LLMs) and other generative AI technologies to build highly effective "first responder" applications. Implement robust RAG (Retrieval Augmented Generation) systems to ground agent responses in accurate, up-to-date, and proprietary organizational data. Workflow Automation: Integrate AI agents with internal business systems (e.g., Slack, Jira, Salesforce, CRM, ERP) using APIs to enable autonomous actions like creating tickets, updating records, or providing status updates. Design and implement agentic workflows that can handle multi-step processes and hand-off tasks to human operators seamlessly when necessary. Prompt Engineering & Agent Design: Develop and optimize sophisticated prompt engineering strategies to ensure agents provide accurate, relevant, and contextually appropriate responses. Design agent personas and interaction models that align with business needs and provide a positive user experience. Data & Knowledge Management : Collaborate with data and content owners to identify, ingest, and manage knowledge bases and data sources essential for agent functionality. Implement strategies for continuous learning and retraining of agents based on user interactions and new data. Performance Monitoring & Optimization: Establish key performance indicators (KPIs) for agent success, such as resolution rate, response time, and user satisfaction. Develop monitoring systems to track agent performance, identify areas for improvement, and mitigate potential issues like "hallucinations" or biased responses. Collaboration & Leadership: Act as a subject matter expert on "first responder" AI solutions, providing technical guidance to cross-functional teams. Work closely with product managers and business stakeholders to identify high-impact use cases and define agent capabilities. Mentor and guide junior engineers in the best practices of agent development. Required Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 3-8 years of professional experience in an AI Engineer, NLP Engineer, or similar role, with a proven track record of deploying conversational or agentic AI solutions to production. Programming: Strong proficiency in Python is non-negotiable. NLP & Generative AI Expertise: Deep, hands-on experience with NLP techniques, including intent recognition, entity extraction, and sentiment analysis. Extensive experience with Large Language Models (LLMs) and fine-tuning using frameworks like Hugging Face Transformers. Practical experience in designing and implementing RAG (Retrieval Augmented Generation) systems. Proficiency in prompt engineering and understanding of various prompt templates and strategies. MLOps & Cloud: Experience with deploying and managing AI agents in a production environment using MLOps practices. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and related services for AI/ML and serverless computing. Familiarity with containerization (Docker) and orchestration (Kubernetes). System Integration: Proven experience integrating AI solutions with external APIs and internal enterprise systems (e.g., Salesforce, Jira, Slack). Problem-Solving

Artificial Intelligence and Machine Learning Engineering – Associate Director, Corporate Technology

Educational Requirements Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities A day in the life of an Infoscion As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight. You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise. You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organizations financial guidelines Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers. If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you! Additional Responsibilities: Ability to develop value-creating strategies and models that enable clients to innovate, drive growth and increase their business profitability Good knowledge on software configuration management systems Awareness of latest technologies and Industry trends Technical and Professional Requirements: Primary skills:Technology->Artificial Intelligence->Computer Vision,Technology->Big Data->Natural language processing(NLP),Technology->Machine Learning->Python Preferred Skills: Technology->Big Data->Natural language processing(NLP) Technology->Machine Learning->Python Technology->Artificial Intelligence->Computer Vision Technology->Machine Learning->Generative AI

About Info Edge: InfoEdge's mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behaviour, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. * About BU: Corporate Function * Required Educational Qualification: PhD/ MTech / BTech with relevant experience from Tier 1 Campus only. * Desired Experience: 0 - 5 Years * Job Objective: You will be building innovative Machine Learning solutions for vital and complex business problems. *Fill this form to proceed further: ( https://tinyurl.com/FAIscientist ) Job Description: As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data. Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs.

KEY RESPONSIBILITIES Lead, manage, and mentor a high-performing team of data scientists, ensuring excellence in technical execution and professional development Define, implement, and refine the AI and ML strategy and roadmap, aligning with the organization's long-term goals and evolving business needs Drive the development and deployment of state-of-the-art AI methodologies, leveraging the latest advancements in machine learning, artificial intelligence, and computational techniques Present complex, data-driven insights and strategic recommendations to stakeholders, driving high-level decision-making Develop and nurture relationships with business partners and stakeholders across the organization, ensuring effective collaboration and alignment on AI-driven projects Ensure the scalability, reliability, and robustness of AI solutions through advanced model development, deployment, and monitoring practices Proactively manage project risks and mitigate potential issues, ensuring successful delivery and alignment with strategic goals Conduct pioneering research in emerging areas, integrating new technologies and methodologies to solve complex business problems Pre-Requisites 12+ years of experience in AI, Data Science or a related field, with a proven track record of leading and executing high-impact, technically complex projects Extensive expertise in advanced machine learning algorithms, deep learning, statistical modeling, and AI, with hands-on experience in cutting-edge techniques Mastery of programming languages such as Python, with extensive experience in advanced machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Keras, LangChain, Transformers, OpenAI SDK, or Hugging Face) Advanced skills in SQL and hands-on experience with big data technologies Deep understanding of LLMs, prompt engineering, and transformer architectures Prior experience leading Generative AI solutions utilizing LLMs such as GPT, Claude, and LLaMA Demonstrated expertise in MLOps practices, including model deployment, monitoring, and optimization at scale Outstanding communication skills, both written and verbal, with the capability to convey complex technical concepts to diverse audiences and influence executive decision-making Ability to manage and deliver multiple high-stakes projects simultaneously, with a deep understanding of how to align data science initiatives with overarching business objectives and strategies (Preferred) Masters degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Marketing Research

Job Title: Senior Data Scientist AI & Generative AI Azure / AWS Location: Bangalore, Whitefield (Hybrid mode 2 days WFO) Experience: 5 to 12 years Role Overview We are seeking an experienced Data Scientist with strong expertise in AI/ML, Generative AI (GenAI), and Microsoft Azure cloud services . The role involves designing, developing, and deploying advanced AI solutions leveraging LLMs, generative models, and Azure-native services to deliver business impact at scale. Key Responsibilities Design and implement AI/ML models , including LLMs and generative AI architectures (e.g., GPT, Diffusion Models). Build and optimize end-to-end AI pipelines on Azure using services like Azure Machine Learning, Azure OpenAI Service, Cognitive Services, Data Factory, and Synapse Analytics . Develop custom AI solutions for NLP, computer vision, and multimodal applications. Integrate GenAI capabilities into enterprise applications using APIs and frameworks. Ensure model governance, security, and compliance in Azure environments. Mentor junior team members and provide technical leadership in AI/ML projects. Stay updated on emerging AI/GenAI trends and Azure AI services . Required Skills Programming: Python (Pandas, NumPy, Scikit-learn), PyTorch/TensorFlow. AI/ML Expertise: Deep learning, NLP, LLM fine-tuning, prompt engineering, generative models. GenAI Tools: Hugging Face, LangChain, Azure OpenAI Service. Azure Cloud: Azure Machine Learning, Azure OpenAI, Cognitive Services, Data Factory, Synapse, Azure Functions. Data Handling: SQL, NoSQL, data lakes, ETL pipelines. MLOps: CI/CD for ML, model deployment, monitoring. Strong understanding of statistics, probability, and optimization techniques .

Lead IBM into the future by translating system requirements into the design and development of customized systems in an agile environment. The success of IBM is in your hands as you transform vital business needs into code and drive innovation. Your work will power IBM and its clients globally, collaborating and integrating code into enterprise systems. You will have access to the latest education, tools and technology, and a limitless career path with the world’s technology leader Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Develop and deploy models using CML workspaces, Build CI/CD pipelines for ML lifecycle Integrate with governance and monitoring tools,Enable secure model serving via REST APIs Preferred technical and professional experience Model governance, lineage, and versioning API exposure for real-time inference

Conducting classroom Training on programming skills Creating a positive and engaging learning environment A passion for teaching and helping students achieve their career goals Strong knowledge of SQL. Python, Data Science, ML, DL, NLP, Power Bi

Preferred candidate profile Proficiency in Python/R, SQL, and data analysis libraries Strong understanding of statistics, machine learning, Deep Learning , Artifical Intelligence,Github and data visualization Experience with cloud platforms (AWS, GCP, or Azure) is a plus Excellent communication and presentation skills Patience and adaptability to different learner needs Perks and benefits Compensation and Benefits

Role: Senior Data Scientist Location: Hyderabad Notice Period: Immediate to 15days About the Role We are looking for a Senior Data Scientist to design and build intelligent chatbot systems that can interpret natural language queries and interact with structured and unstructured data using Text-to-SQL, RAG (Retrieval-Augmented Generation), and Agentic reasoning. Youll lead the development of multi-modal, context-aware, and autonomous agents that use large language models to query databases, invoke tools, retrieve knowledge, and plan actions, all within enterprise-grade environments. Key Responsibilities Build Text-to-SQL agents that convert natural language into accurate, executable SQL across various schemas. Design RAG pipelines to enrich LLM outputs using internal documents, tables, and API-based retrievers. Develop agentic frameworks that enable tool use, database interaction, planning, and task decomposition using LLMs. Tune prompts and build evaluation systems for accuracy, latency, grounding, and correctness. Work with product and data teams to build domain-specific few-shot examples, tool definitions, and vectorized schema representations. Optimize inference latency using frameworks like LangChain, Semantic Kernel, or Llama Index. Required Skills 4+ years in Data Science or NLP, with 2+ years in LLM-based application development. Experience with Text-to-SQL modeling (Spider, BIRD, etc.) and fine-tuning using synthetic or annotated query datasets. Strong understanding of LLM orchestration tools (LangChain, Semantic Kernel, or custom agents). Hands-on with RAG architectures: embedding generation, retriever tuning, chunking strategies, and reranking. Proficiency in Python, SQL, and vector search tools (FAISS, Pinecone, Weaviate, OpenSearch). Familiarity with prompt tuning, structured output parsing, and function calling (OpenAI, Mistral, Anthropic, etc.). Leadership & Collaboration Lead experimentation and architectural design for agent-based workflows (SQL agents, document agents, hybrid search agents). Mentor junior team members in LLM prompt engineering, schema design, and text- to-structure pipelines. Collaborate with ML engineers, product managers, and data owners to implement scalable conversational AI interfaces. Nice to Have Experience with vLLM, LoRA fine-tuning, or quantized model deployment. Prior work in multi-agent planning, self-healing agents, or semantic query generation. Familiarity with tools like SQLGlot, DSPy, DeepEval, and OpenAI function tools. Knowledge of structured RAG (combining structured + unstructured sources) and hybrid ranking.

The Opportunity As the Global Practice Lead AI, you will lead the global strategy, development, and delivery of AI solutions centered around Nutanix Enterprise AI (NAI). This role demands deep expertise in generative AI, LLMOps, and hybrid cloud architectures, with a strong focus on operational simplicity, scalability, and enterprise-grade security. You will drive innovation, build high-performing practice team spanning across geos, and ensure successful client outcomes across industries. The Global Practice Lead for AI is expected to bring a strong foundation in deep expertise in delivering enterprise-grade AI solutions across industries especially in terms of the infrastructure needs in AI. Expertise in machine learning, deep learning, generative AI, NLP and cloud-based AI platforms with working knowledge of Kubernetes is expected. As the Global Practice Lead AI, you will be responsible for building, scaling, and leading the AI practice globally. You will define the strategic direction, develop service offerings, drive innovation, and ensure delivery excellence across engagements. This role requires deep technical expertise in AI technologies, strong business acumen, and proven leadership in managing global teams and client relationships. The role focuses on thought leadership, pre-sales, and intellectual property creation in the arena of an cloud and automation consulting practice. Additionally, the Practice contributes to the optimization of service delivery and delivery processes. You will not be managing consultant resources, the scheduling of customer delivery jobs, or the financial aspects of revenue attainment from delivery. Your Role Work with Services Product Management to develop the catalog of service offerings delivered by both Nutanix and Partner consultants. Lead the development of service SKUs, delivery toolkits, and level or effort for all products in the portfolio. Develop repeatable best practices and design guides based upon common customer experiences and solutions. Work with the Services Practice Development team to keep items current and develop training programs to enable the selling and delivery of services. Evangelize Nutanixs vison for hybrid and Enterprise Cloud and software defined datacenter. Develop yearly training plans for practice consultants and track attainment of the training goals. Review statements of work and be responsible for validating services level of effort in the pre-sales process, on AI services offerings. In larger pursuits, work Services Sales Managers and Architects to construct class-leading, complex global outcomes. Provide technical presales expertise on complex and/or custom professional services offerings and solutions. Develop customer trends and common use cases for our product and services, especially within areas of subject matter expertise. Work with Nutanix customers to understand business goals and translate them into technical solutions based upon Nutanix product. Work with Nutanix Product Managers and Enterprise Architects to create service offerings that properly map back to new and existing consulting product offerings. Working closely and foster relationships with key clients, Product Management, Product Engineering, and the Sales and SE organizational leaders. Drive and manage KPI for practice consulting attach and incremental corporate value. Lead and refine opportunity plans and grow the surface area for campaigns aligning with the corporate mission. Participate in sales and revenue forecasts, quarterback creative ways to provide customer value, and stay abreast of status/details for each campaign and opportunity where your involvement guarantees a successful outcome. Monitor practice consulting CSAT, delivery quality, and follow up with white glove service on deficient areas where necessary. Monitor practice consulting offer delivery margin and adherence to expected level of effort for standard offerings and take corrective action when necessary. Deliver Platform consulting solutions to key Clients and projects where necessary. The expected billable percentage is 20%. What You Will Bring 15+ years of experience in data driven IT services with at least 3 years AI technologies. Proven experience in practice management and delivering enterprise-grade AI solutions across multiple industries. Proven experience in deploying GenAI solutions using Kubernetes, LLM APIs, and hybrid cloud platforms. Expertise in LLMOps, model monitoring, RBAC, and secure API workflows. Familiarity with Nutanix Cloud Infrastructure, Kubernetes Platform, and Unified Storage will be a big plus. Expertise in machine learning, deep learning, generative AI, NLP, computer vision, and cloud-based AI platforms. Strong understanding of AI ethics, governance, and regulatory frameworks. Working knowledge of Kubernetes, containers, CI/CD, DevOps, and cloud platforms (AWS, Azure, GCP). Strong understanding of enterprise architecture, application modernization, and agile delivery. Excellent leadership, communication, and stakeholder management skills. Bachelors or masters degree in computer science, Engineering, or related field; certifications in AI, analytics, data, cloud-native technologies are a plus. Excellent understanding of hybrid cloud modalities, IT go-to market challenges, and business drivers that impact customer purchasing decisions Proven experience in designing AI solutions based upon customer requirements, hosted on cloud architecture in a Premier account portfolio Natural leadership abilities, ability to thrive in an independent manner combining exceptional interpersonal communication, virtual team building, and presentation skills Ability to whiteboard solutions interactively with customers and develop robust architectural documentation Ability to analyze contractual and commercial constructs of a services engagement, Enterprise Purchase Agreements (EPA), working with extended account teams in a potentially multi-vendor arrangement Strong communications skills, both verbal and written, with the ability to engage and win the confidence of C-Level executives, Geo leads, Sales Managers, Enterprise Architects and Service Delivery Managers. Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.

ZS Advanced Data Science - Associate ZS is a place where passion changes lives. As a management consulting and technology firm focused on transforming global healthcare and beyond, our most valuable asset is our people. Here youll work side-by-side with a powerful collective of thinkers and experts shaping solutions from start to finish. At ZS, we believe that making an impact demands a different approach; and thats why here your ideas elevate actions, and here youll have the freedom to define your own path and pursue cutting-edge work. We partner collaboratively with our clients to develop products that create value and deliver company results across critical areas of their business including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy and many more. If you dare to think differently, join us, and find a path where your passion can change lives. Our most valuable asset is our people . At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems the ones that comprise us as individuals, shape who we are and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. About Advanced Data Science (ADS): ZS Advanced Data Science group is focused on creating practical impact for clients across various industries such as Healthcare and Bio-Tech, Hi-Tech & Telecommunication, Financial Services and Travel through advanced analytics and emerging data sources. Emerging datasets include both unstructured datasets (for example, text, voice, image, etc.) and semi-structured datasets (for example, patient-level records). Advanced analytical techniques span a range of innovative machine learning, artificial intelligence, advanced statistics and optimization approaches. Being part of the ADS group at ZS will be an opportunity for you to work on cutting-edge solutions, utilizing new age data sources to shape innovations across multiple areas, for our clients and the broader ZS community. A key enabler of our services is leveraging data in delivering client solutions. The data available about customers is getting richer and the problems that our customers are trying to answer continue to evolve. In our endeavor to stay ahead in providing solutions to these evolving complex problems, ZS has set up an Advanced Data Science which has three major focus areas: • Research the evolving datasets and advanced analytical techniques to develop new offerings/solutions • Deliver client impact by collaboratively implementing these solutions • Provide thought leadership by developing the ZS Point of View in this space Data Science Associate Data Science Associate (DSA) design, develop and execute high-impact analytics solutions for large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. Responsibilities: Develop advanced algorithms that solve problems of large dimensionality in a computationally efficient and statistically effective manner • Execute statistical and data mining techniques (e.g. hypothesis testing, machine learning and retrieval processes) on large data sets to identify trends, figures and other relevant information • Collaborate with clients and other ZS stakeholders to effectively integrate and communicate analysis findings • Contribute to the evaluation of emerging datasets and technologies that may contribute to our analytical platform • Evaluating emerging datasets and technologies that may contribute to our analytical platform • Owning the development of select assets/accelerators for efficient scaling of capability, with a focus on leveraging generative AI and deep learning methodologies. • Integrate engineering principles into data science workflows, optimizing algorithms for performance, scalability, and maintainability. • Collaborate with the engineering team to implement and deploy data science solutions into production, ensuring seamless integration with existing systems. • Utilize software engineering best practices for version control, code review, testing, and documentation to maintain high-quality, reliable, and reproducible data science workflows. Qualifications: Bachelor's or master's degree or PhD in Computer Science (or Statistics) from a premier institute, and strong academic performance with analytic and quantitative coursework is required. • 1-3 years of Data Science experience, including proficiency in generative AI, deep learning, statistical techniques, and engineering integration for scalable solutions. • Knowledge of programming (e.g. Java/Python/R); • Knowledge of big data/advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modeling, etc.); • Excellent oral and written communication skills. • Strong attention to detail, with a research-focused mindset; • Excellent critical thinking and problem-solving skills; • High motivation, good work ethic and maturity. • Exposure to Generative AI and its usage to solve problems is a plus. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Considering applying? At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact in global healthcare and beyond. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At: www.zs.com

Role & responsibilities AI/ML Integration: Incorporate machine learning libraries like TensorFlow or PyTorch for personalized learning experiences, predictive analytics, and automated grading. Design, develop, and deploy AI/ML models for business applications. Analyze large datasets to extract meaningful insights and patterns. Integrate AI solutions into existing and new products/ services. Optimize models for performance, scalability, and accuracy. Stay updated with the latest advancements in AI and apply emerging techniques. Conduct research and experimentation to improve existing algorithms. Collaborate with frontend teams to integrate AI features using React.js and PWA. Ensure seamless integration with PostgreSQL databases. Develop and integrate APIs for AI model consumption. Preferred candidate profile Bachelors or Master’s degree in Computer Science, Data Science, AI, or related field. 1+ years of experience in AI/ML development. Strong understanding of supervised, unsupervised, and reinforcement learning. Experience with NLP, computer vision, or recommendation systems. Proficiency in data preprocessing, feature engineering, and model evaluation. Familiarity with model deployment and monitoring in production environments. Experience with generative AI and LLMs. Knowledge of MLOps practices. Contributions to open-source AI projects.

Role & responsibilities Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Preferred candidate profile Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

About Company Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India. Job Description As a Senior Data Scientist, you will be responsible for providing simple and intuitive solutions to the most complex problems in renewable industry. This will involve building machine learning and deep learning models which are coupled with contextual business knowledge. You will also use both management experience and data science expertise to lead analytics projects and mentor junior data scientists . You will be an integral part of conceptualizing, scoping and delivering complex analytics projects . You will do and oversee the development, testing and maintenance of analytical models which mimic business decisions. You will work with a world-class team of site managers, subject experts, data engineers and data scientists to build the next generation data-driven renewable company. Additionally, you will be responsible for continuously identifying opportunities to improve the ways of working and structuring within the analytics center of excellence. Roles and Responsibilities Implement data science solutions which may involve machine learning or data science techniques to increase and optimize outputs Assess the effectiveness and accuracy of data sources and data gathering techniques Manage analytics strategy across multiple use cases Provide analytical expertise in the process of model development, refining and implementation in a variety of analytics problems spread across a variety of domains Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution Work closely with translators and business teams to develop and implement analytics solutions Collaborate with the engineering team to integrate data science solutions into production environments and deploy scalable solutions Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner Acquire extensive knowledge of renewables industry practices and implement tailor made techniques to solve problems relevant to the same Promote a culture of continuous learning, sharing knowledge, and staying up-to-date with emerging technologies and best practices in data science Profile & Eligible Criteria Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field. Master's degree preferred Proven experience of 4-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI Proficiency in Python is a must. Proficiency in SQL for data manipulation is a plus Worked in developing analytics solutions in 3-4 domains Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams Communication skills: Basic level of articulation of theoretical concepts Ability to communicate with cross functional roles is a plus Teamwork: Displays ability to work both as an individual and as a self-motivated team player Has worked in large teams with an agile setup in the past

Experience : 5 - 8 years Preference : Immediate joiners or candidates serving notice period (September joiners preferred) We are looking for a Senior Data Scientist with strong expertise in Generative AI (GenAI) and Classical Machine Learning (ML) to drive innovation and deliver cutting-edge AI/ML solutions. This role involves designing and implementing GenAI models and scalable ML pipelines to solve business problems and enhance productivity. Key Responsibilities Design, build, and fine-tune Generative AI models using LLMs (e.g., GPT, LLaMA, Claude, PaLM) for applications such as summarization, content generation, semantic search, and question answering. Develop end-to-end AI solutions, including prompt engineering, fine-tuning, evaluation, and deployment. Build Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain, LlamaIndex, and vector databases (FAISS, Pinecone, Weaviate). Apply Classical ML techniques for forecasting, optimization, and predictive modeling across business use cases. Collaborate with product, engineering, and business teams to identify opportunities, prototype solutions, and deliver impact-driven AI projects. Conduct experiments, evaluate model performance, and optimize for accuracy, scalability, and latency. Contribute to the development of GenAI and ML best practices and reusable frameworks within the organization. Stay updated on the latest research and advancements in LLMs, GenAI, and ML. Required Skills and Experience 58 years of experience in Data Science or AI roles. Minimum 2+ years of hands-on experience in GenAI or LLMs. Strong proficiency in Python with frameworks such as Hugging Face, Transformers, PyTorch, or TensorFlow. Deep understanding of NLP, LLMs, and generative techniques. Experience in prompt engineering, fine-tuning, and few-shot learning. Hands-on expertise with LangChain, LlamaIndex, or similar orchestration frameworks. Knowledge of vector stores, embeddings, and retrieval techniques. Experience with cloud platforms (AWS, Azure, GCP) and model deployment. Familiarity with MLOps practices is a plus. Preferred Qualifications Masters or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field. Experience with OpenAI, Anthropic, Meta AI, or Google GenAI APIs. Prior experience in building chatbots, copilots, or enterprise GenAI applications. Contributions to open-source projects or publications in GenAI.

Job Application Link: https://app.fabrichq.ai/jobs/f3915b50-d4cf-4d45-865b-fedcbd509635 Job Summary: A senior engineering role focused on designing, developing, and deploying advanced AI models with emphasis on generative AI and transformer architectures. The position involves working with complex datasets, implementing and fine-tuning models in production environments, and collaborating with cross-functional teams to create AI solutions tailored to business needs. Key Responsibilities Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures and deep learning models Work with extensive and complex datasets, performing cleaning, preprocessing, and transforming data for generative model training Collaborate with cross-functional teams to identify project objectives and create generative AI solutions tailored to business needs Implement, fine-tune, and scale generative AI models in production environments Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment Stay informed about the latest advancements in generative AI research and apply new findings to improve models Document and communicate technical specifications, algorithms, and project outcomes to stakeholders Skills & Requirements Must Have Skills Language models Python programming with AI/ML libraries (Hugging Face Transformers, PyTorch, TensorFlow) Machine learning algorithms and deep learning Generative AI techniques Data processing for training large language models Model deployment in production environments

About the Role Youll own the architecture, development, and deployment of next-generation scalable agentic AI systems that reshape how organizations operate. These solutions will autonomously orchestrate multi-step workflows, analyze real-time data streams, surface predictive insights, and embed decision-making across finance, sales, operations, and more. Youll partner with product, data science, RPA, security, and business teams to drive end-to-end impact. Responsibilities Develop robust, production-grade AI agents tailored to solve real-world enterprise challenges. Collaborate across technical and business teams to ensure agent success at every stage. Design serverless, event-driven workflows usingAzure Functions,Logic Apps, andPower Automate. Build data pipelines and train ML models (predictive analytics, anomaly detection, recommendation engines) usingAzure ML,Databricks, andPython. Integrate AI agents with enterprise systems likeSAP HANA,Salesforce,Snowflake,Kafka, andRPA platforms (UiPath)for seamless data exchange. Establish observability, monitoring, and alerting usingAzure Monitorto meet SLAs and reliability targets. Define architecture patterns, reusable components, and governance frameworks to ensure security, compliance, and scalability. Lead code reviews, mentor junior engineers, and champion best practices in version control (Git) and agile ceremonies. LeverageMicrosoft AI Foundryto build and deploy AI agents, ensuring they meet enterprise standards and requirements. Copilot Studio (Optional) Cross-Functional Collaboration Work closely with: Data Scientists & Machine Learning Engineers for model development and integration Scrum Masters, QA Engineers & DevOps Personnel to ensure smooth delivery and deployment Product Managers aligning agent capabilities with business goals UX Designers crafting intuitive agent interactions and interfaces Enterprise Architects ensuring scalability and ecosystem alignment Security & Compliance Teams meeting regulatory and governance requirements Business Stakeholders / SMEs defining agent use cases and validating outcomes Change Management & Enablement Teams supporting adoption and training efforts Technology & Tools Languages & Platforms: Python, Power Apps, Power Automate, Databricks, Snowflake Enterprise Systems: SAP HANA, Kafka, UiPath AI Platforms: Microsoft AI Foundry (highly preferred), Copilot Studio (optional) Cloud & ML Tools: Azure Machine Learning, Azure DevOps, GitHub Data & Observability: Vector Databases, Azure Monitor What You Bring A strong sense of ownership and responsibility Ability to work autonomously within cross-functional teams Maturity in navigating complex systems and dynamic priorities Passion for building transformative AI systems and solving meaningful problems

As an Intern, your responsibilities will include: Collaborating within teams to solve high-level business challenges Conducting essential research and analysis Performing complex quantitative, strategic, and financial assessments of corporations and industries Receiving mentorship to develop leadership and client management capabilities Gaining broad exposure to various topics and industries within our consulting services Immediate impact, continuous challenge You will contribute to impactful projects that influence clients, industries, and society at large Challenging the status quo and striving to innovate, you will help shape the future of our firm and the world around us As a valued team member from the outset, you will build trust-based relationships with stakeholders and deliver breakthrough results Each project helps you expand your skillset and collaborate with specialists possessing deep subject-matter expertise Chart your course; we support the journey You will have the chance to work on diverse projects (1 to 2 projects depending on the project duration) Throughout your internship, you will be guided and mentored by colleagues, including a buddy, and your talent manager We hire you to be you We foster an open, inclusive, and down-to-earth environment that encourages you to bring your authentic self to work You will collaborate with approachable colleagues who are committed to serious work but maintain a sense of humility and humor Our culture eschews rigid hierarchies and artificial barriers, ensuring equal opportunities for personal and professional growth

Role & responsibilities Understand workflows/processes and devise strategies for the areas applicable to AI-based implementation. Translate eLearning requirements into AI-driven automation strategies. Define data requirements and provide datasets for AI model training specific to eLearning. Design and maintain data pipelines (Azure Data Factory, Databricks, Synapse Analytics) to ensure clean, structured content for training. Apply governance frameworks (Azure Policy, Purview, DLP) to ensure responsible AI practices. Ensure fairness and transparency in AI models using Fair learn and Interpret ML. Develop and optimize AI models for automating eLearning processes, including interactive storyboards, content creation/development, and adaptive/customised learning paths. Leverage Azure Cognitive Services, Machine Learning Studio, and Azure OpenAI for scalable eLearning solutions. Use Adobe/other AI tools for automating audio narration, translation, video editing, and image creation for eLearning modules. Implement AI-driven workflows for converting text-based content into engaging eLearning assets. Design guardrails for ethical AI use in eLearning, ensuring compliance with GDPR and ISO 27001. Implement secure environments with Azure Key Vault, Security Center, and RBAC. Deploy AI models using Azure Machine Learning Pipelines and monitor performance. Set up CI/CD workflows for continuous optimization and scaling of AI solutions. Integrate AI into LMS and CMS primarily through APIs and custom integrations (with an extensibility consideration for integrating it with other platforms like Project Management Tool, Dashboards, etc.) Build AI-powered plugins for automating course creation, learner analytics, and feedback. Document AI workflows and provide training, architecture diagrams, and code snippets for team members. Preferred candidate profile At least 5-8 years of experience deploying Machine Learning and Generative AI models into production with operational support. Advanced knowledge of Machine Learning and LLMs (e.g., GPT, Llama), with experience in LangChain, RAG, and model tuning. Proficient in MLOps tools (e.g., ML flow) for lifecycle management of machine learning models. Strong programming skills in Python, JavaScript, and RESTful APIs, with clean, efficient coding for AI Assistant and platform integrations. Experience with cloud computing platforms (AWS, Google Cloud, Azure) and cloud-based application deployment for model scaling. Deep knowledge of AI, NLP, and Conversational AI platforms (e.g., Bot Framework, PVA, Cognigy). Proficient in Azure AI Suite, including Cognitive Services, Machine Learning Studio, and other tools. Experience with Fairlearn, InterpretML, and adherence to GDPR, HIPAA, and ISO 27001 standards. Exposure to multimedia automation tools (e.g., Adobe AI tools) for video/image editing workflows. Exposure to eLearning development tools, and processes.

About the Team The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale. Why Join Us Build AI-first observability tools that redefine how engineers triage and troubleshoot. Own systems that reduce hours of manual work in engineering and SRE workflows . Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation. Hybrid work model that supports flexibility and deep focus. Help shape the central AI charter at Nutanix and influence future AI products across the company. Your Role AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panaceas ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency. AI/ML-powered Log Analyzer Tool : Use deep learning (e.g., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users. Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and moreautomatically identifying performance degradation or system regressions across distributed environments. Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures. Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems. LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations. Central AI Charter : Contribute to Nutanixs foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products. Responsibilities Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics. Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization. Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, etc.). Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative. Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring. Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams. Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling. Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices. What You Will Bring Educational Background : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields. Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale. ML Expertise : Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning. Experience building ML models for metrics data (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders. Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization. Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A. Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models. Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK). Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact.

General Summary: Looking for ML framework and AI compiler Engineer responsible for Designing, implementing, and deploying machine learning models using PyTorch Focusing on backend infrastructure and system architecture. Responsibilities often include developing framework, integrating with other AI tools, and ensuring scalability and reliability. Here's a more detailed breakdown of what you might see in such a job description: Key Responsibilities: Model Development and Deployment: Designing, building, and deploying AI models, particularly those leveraging PyTorch for deep learning. Backend Infrastructure: Developing and maintaining the backend systems that power AI applications, including data ingestion, processing, and storage. System Architecture: Designing scalable and high-performance backend architectures to handle AI workloads. Model Optimization: Optimizing model performance for speed, accuracy, and resource efficiency. Integration: Integrating AI models with other systems and applications. API Development: Creating and maintaining APIs for communication between frontend and backend components. Data Handling: Managing data ingestion, preprocessing, and storage for AI training and inference. Collaboration: Working with data scientists, product managers, and other engineers to bring AI solutions to life. Tools, Technologies, Skills and Programming: C, C++: Strong programming capability using advanced techniques to design and develop AI compilers and backends. Scripting: Strong expertise in Python with design, develop, release and maintain projects. AI Frameworks: Familiarity with other AI frameworks like PyTorch, TensorFlow, Hugging Face, etc. Machine Learning Knowledge: Understanding of machine learning principles and algorithms starting Computer vision to large language models and continuously update to new trends. Expertise to deep learning accelerator programming (GPU, NPU). Any parallel programming experience (Like CUDA, OpenCL, MKLDNN ..etc) is a plus. Experience with deep leaning compilers like Glow, TVM etc is a plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. ORMaster's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. ORPhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.