212 Interpretability Jobs - Page 3

Responsibilities Lead 4-8 data scientists to deliver ML capabilities within a Databricks-Azure platform Guide delivery of complex ML systems that align with product and platform goals Balance scientific rigor with practical engineering Define model lifecycle, tooling, and architectural direction Requirements Skills & Experience Advanced ML: Supervised/unsupervised modeling, time-series, interpretability, MLflow, Spark, TensorFlow/PyTorch Engineering: Feature pipelines, model serving, CI/CD, production deployment Leadership: Mentorship, architectural alignment across subsystems, experimentation strategy Communication: Translate ML results into business impact Benefits What you get Best in class salary: We hire only the best, and we pay accordingly Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day This is a contract role based in Abu Dhabi. If relocation from India is required, the company will cover travel and accommodation expenses in addition to your salary About Us Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media and Entertainment companies in the world! We're headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies. We are Proximity — a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company's success will be huge. You'll have the chance to work with experienced leaders who have built and led multiple tech, product and design teams. Here's a quick guide to getting to know us better: Watch our CEO, Hardik Jagda, tell you all about Proximity Read about Proximity's values and meet some of our Proxonauts here Explore our website, blog, and the design wing — Studio Proximity Get behind-the-scenes with us on Instagram! Follow @ProxWrks and @H.Jagda

Position Overview Job Title- Data Science Engineer, AS Location- Bangalore, India Role Description We are seeking a Data Science Engineer to contribute to the development of intelligent, autonomous AI systems The ideal candidate will have a strong background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. This role involves deploying AI solutions that leverage Retrieval-Augmented Generation (RAG) Multi-agent frameworks Hybrid search techniques to enhance enterprise applications. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your Key Responsibilities Design & Develop Agentic AI Applications: Utilise frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. Implement RAG Pipelines: Integrate LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. Fine-Tune Language Models: Customise LLMs (e.g., Gemini, chatgpt, Llama) and SLMs (e.g., Spacy, NLTK) using domain-specific data to improve performance and relevance in specialised applications. NER Models: Train OCR and NLP leveraged models to parse domain-specific details from documents (e.g., DocAI, Azure AI DIS, AWS IDP) Develop Knowledge Graphs: Construct and manage knowledge graphs to represent and query complex relationships within data, enhancing AI interpretability and reasoning. Collaborate Cross-Functionally: Work with data engineers, ML researchers, and product teams to align AI solutions with business objectives and technical requirements. Optimise AI Workflows: Employ MLOps practices to ensure scalable, maintainable, and efficient AI model deployment and monitoring. Your Skills And Experience 4+ years of professional experience in AI/ML development, with a focus on agentic AI systems. Proficient in Python, Python API frameworks, SQL and familiar with AI/ML frameworks such as TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms (e.g., GCP, AWS). Experience with LLMs (e.g., GPT-4), SLMs (Spacy), and prompt engineering. Understanding of semantic technologies, ontologies, and RDF/SPARQL. Familiarity with MLOps tools and practices for continuous integration and deployment. Skilled in building and querying knowledge graphs using tools like Neo4j. Hands-on experience with vector databases and embedding techniques. Experience in developing AI solutions for specific industries such as healthcare, finance, or e-commerce. How We’ll Support You Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Responsibilities Lead 4-8 data scientists to deliver ML capabilities within a Databricks-Azure platform Guide delivery of complex ML systems that align with product and platform goals Balance scientific rigor with practical engineering Define model lifecycle, tooling, and architectural direction Requirements Skills & Experience Advanced ML: Supervised/unsupervised modeling, time-series, interpretability, MLflow, Spark, TensorFlow/PyTorch Engineering: Feature pipelines, model serving, CI/CD, production deployment Leadership: Mentorship, architectural alignment across subsystems, experimentation strategy Communication: Translate ML results into business impact Benefits What you get Best in class salary: We hire only the best, and we pay accordingly Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day About Us Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media and Entertainment companies in the world! We're headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies. We are Proximity — a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company's success will be huge. You'll have the chance to work with experienced leaders who have built and led multiple tech, product and design teams. Here's a quick guide to getting to know us better: Watch our CEO, Hardik Jagda, tell you all about Proximity Read about Proximity's values and meet some of our Proxonauts here Explore our website, blog, and the design wing — Studio Proximity Get behind-the-scenes with us on Instagram! Follow @ProxWrks and @H.Jagda

Responsibilities Lead 4-8 data scientists to deliver ML capabilities within a Databricks-Azure platform Guide delivery of complex ML systems that align with product and platform goals Balance scientific rigor with practical engineering Define model lifecycle, tooling, and architectural direction Requirements Skills & Experience Advanced ML: Supervised/unsupervised modeling, time-series, interpretability, MLflow, Spark, TensorFlow/PyTorch Engineering: Feature pipelines, model serving, CI/CD, production deployment Leadership: Mentorship, architectural alignment across subsystems, experimentation strategy Communication: Translate ML results into business impact Benefits What you get Best in class salary: We hire only the best, and we pay accordingly Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day About Us Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media and Entertainment companies in the world! We're headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies. We are Proximity — a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company's success will be huge. You'll have the chance to work with experienced leaders who have built and led multiple tech, product and design teams. Here's a quick guide to getting to know us better: Watch our CEO, Hardik Jagda, tell you all about Proximity Read about Proximity's values and meet some of our Proxonauts here Explore our website, blog, and the design wing — Studio Proximity Get behind-the-scenes with us on Instagram! Follow @ProxWrks and @H.Jagda

Bosch Software Engineering, Data Science Pune, Maharashtra, India Posted on Jul 14, 2025 Apply now Company Description Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 28,200+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region. Job Description Education and Work Experience Requirements: 5 to 8 years of experience as Data Scientist· 2 to 3 years of experience in Generative AI solution development· Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making. Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments. Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents. Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows. Hands-on experience integrating LLMs (GPT, LLaMA, Mistral, etc.) with agentic frameworks to enhance automation and reasoning. Expertise in hierarchical agent frameworks, distributed agent coordination, and decentralized AI governance. Strong grasp of memory architectures, tool use, and action planning within AI agents. Autonomy Score: Measures the degree of independence in decision-making. Collaboration Efficiency: Evaluates the ability of agents to work together and share information. Task Completion Rate: Tracks the percentage of tasks successfully executed by agents. Response Time: Measures the latency in agent decision-making and execution. Adaptability Index: Assesses how well agents adjust to dynamic changes in the environment. Resource Utilization Efficiency: Evaluates computational and memory usage for optimization. Explainability & Interpretability Score: Ensures transparency in agent reasoning and outputs. Error Rate & Recovery Time: Tracks failures and the system’s ability to self-correct. Knowledge Retention & Utilization: Measures how effectively agents recall and apply information. Hands-on experience with LLMs such as GPT, BERT, LLaMA, Mistral, Claude, Gemini, etc. Proven expertise in both open-source (LLaMA, Gemma, Mixtral) and closed-source (OpenAI GPT, Azure OpenAI, Claude, Gemini) LLMs. Advanced skills in prompt engineering, tuning, retrieval-augmented generation (RAG), reinforcement learning (RAFT), and LLM fine-tuning (PEFT, LoRA, QLoRA). Strong understanding of small language models (SLMs) like Phi-3 and BERT, along with Transformer architectures. Experience working with text-to-image models such as Stable Diffusion, DALL·E, and Midjourney. Proficiency in vector databases such as Pinecone, Qdrant for knowledge retrieval in agentic AI systems. Deep understanding of Human-Machine Interaction (HMI) frameworks within cloud and on-prem environments. Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs. Expertise in Python, R, TensorFlow, Keras, and PyTorch. Hands-on experience with NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Knowledge Graphs, and LLM-based applications. Proficiency in advanced statistical methods and transformer-based text processing. Experience in reinforcement learning and planning techniques for autonomous agent behavior. Mandatory Skills: Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails· Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. Experience in cloud services like Azure, GCP and AWS· Multi-agent frameworks: AutoGen, LangGraph, LangChain, CrewAI· Large Language Models (LLMs): GPT, Qualifications BE,B Tech, MTech Additional Information 7-11 years Apply now See more open positions at Bosch

Job Description Join our team as a Generative AI Architect in the AI Practice! We are looking for a visionary individual to lead the design, development, and deployment of cutting-edge Generative AI solutions, driving business value across our products and services. Key Responsibilities : Lead generative AI initiatives in text, ASR, TTS & STT generation and develop AI pipelines and ML models. Design scalable AI systems using state-of-the-art generative models like LLMs and diffusion models. Collaborate with cross-functional teams to integrate generative AI into business workflows. Define best practices for model lifecycle management, focusing on data preparation, training, evaluation, deployment, and monitoring. Guide ethical AI development with a focus on fairness, interpretability, and compliance. Qualifications: Bachelor’s or Master’s degree in Computer Science or related field. 7+ years of AI/ML development experience, with 2+ years in generative AI. Hands-on experience with large language models and diffusion models. Strong proficiency in Python and ML frameworks. Experience with Azure, GCP, and containerization. Familiarity with AI architecture patterns and model fine-tuning. Knowledge of data privacy laws and AI ethics principles. Preferred: Experience deploying GenAI applications in production. Knowledge of vector databases and retrieval-augmented generation. Experience with CI/CD pipelines for ML Job Type: Full-time Work Location: In person

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Years of Experience: Candidates with 15+ years of hands on experience Required Skills Must Have: Solid knowledge and experience of supervised, unsupervised machine learning algorithms. For e.g (but not limited to): linear regressions, bayesian regressions, multi objective optimization techniques, classifiers, cluster analysis, dimension reduction etc. Understanding of technicality used for retail analytics across loyalty, customer analytics, assortment, promotion and marketing Good knowledge of statistics For e.g: statistical tests & distributions Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib) Advanced level programming in SQL and Python/Pyspark to guide teams Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. Nice To Have Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow) Experience with model explainability and interpretability techniques Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product Ability to think through complex user scenarios and design simple yet effective user interactions Good Communication and presentation skills Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Years of Experience: Candidates with 15+ years of hands on experience Required Skills Must Have: Solid knowledge and experience of supervised, unsupervised machine learning algorithms. For e.g (but not limited to): linear regressions, bayesian regressions, multi objective optimization techniques, classifiers, cluster analysis, dimension reduction etc. Understanding of technicality used for retail analytics across loyalty, customer analytics, assortment, promotion and marketing Good knowledge of statistics For e.g: statistical tests & distributions Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib) Advanced level programming in SQL and Python/Pyspark to guide teams Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. Nice To Have Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow) Experience with model explainability and interpretability techniques Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product Ability to think through complex user scenarios and design simple yet effective user interactions Good Communication and presentation skills Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Years of Experience: Candidates with 15+ years of hands on experience Required Skills Must Have: Solid knowledge and experience of supervised, unsupervised machine learning algorithms. For e.g (but not limited to): linear regressions, bayesian regressions, multi objective optimization techniques, classifiers, cluster analysis, dimension reduction etc. Understanding of technicality used for retail analytics across loyalty, customer analytics, assortment, promotion and marketing Good knowledge of statistics For e.g: statistical tests & distributions Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib) Advanced level programming in SQL and Python/Pyspark to guide teams Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. Nice To Have Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow) Experience with model explainability and interpretability techniques Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product Ability to think through complex user scenarios and design simple yet effective user interactions Good Communication and presentation skills Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

Job Summary: We are looking for a highly skilled and motivated AI/ML Expert to lead the development and deployment of advanced machine learning models and AI solutions. The ideal candidate will have strong experience in data science, deep learning, and AI engineering, and will be responsible for designing intelligent systems that solve real-world business problems. Key Responsibilities: Design, build, and deploy scalable machine learning and deep learning models. Work on projects involving supervised, unsupervised, and reinforcement learning. Collect, clean, and preprocess large-scale structured and unstructured datasets. Research and prototype cutting-edge AI techniques (e.g., NLP, computer vision, generative models). Collaborate with data engineers, product managers, and software developers to integrate AI solutions into production. Monitor and evaluate model performance, and implement improvements as needed. Stay up-to-date with the latest AI/ML research, tools, and technologies. Develop and maintain reusable ML pipelines and model lifecycle management. Ensure ethical AI development practices, including model interpretability and fairness. Required Qualifications: Graduate BE/B.Tech and Postgraduate - MCA/MTech with specialization in computers /Electronics /IT or M.Sc.in CS/IT/Physics/Mathematics/Stats / Electronics Language-: JS , Python , HTML5/CSS, Platform-: MySQL , PostgreSQL, Tools-: ML Tools and Libraries, Expertise-: API Integration Expert 3+ years of experience in AI/ML development and deployment . Proficiency in programming languages such as Python (e.g., scikit-learn, TensorFlow, PyTorch), R, or Julia. Experience with deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). Strong understanding of statistics, linear algebra, and optimization techniques. Experience with cloud platforms like AWS, GCP, or Azure. Proficient in using data science tools and libraries (NumPy, Pandas, OpenCV, spaCy, Hugging Face, etc.). Job Type: Contractual / Temporary Contract length: 12 months Pay: ₹85,000.00 - ₹90,000.00 per month Benefits: Provident Fund Schedule: Day shift Work Location: In person

Senior Artificial Intelligence Developer Location: Pune Experience: 3–8 Years Company: Asmadiya Technologies Pvt. Ltd. About the Role Asmadiya Technologies is seeking a Senior AI Developer to lead the design and deployment of advanced AI solutions across enterprise-grade applications. You will architect intelligent systems, mentor junior engineers, and drive innovation in the areas of machine learning, deep learning, computer vision, and large language models. If you're ready to turn AI research into impactful production systems, we want to work with you. Key Responsibilities Lead end-to-end design, development, and deployment of scalable AI/ML solutions in production environments. Architect AI pipelines and integrate models with enterprise systems and APIs. Collaborate cross-functionally with product managers, data engineers, and software teams to align AI initiatives with business goals. Optimize models for performance, scalability, and interpretability using MLOps practices. Conduct deep research and experimentation with the latest AI techniques (e.g., Transformers, Reinforcement Learning, GenAI). Review code, mentor team members, and set technical direction for AI projects. Own model governance, ethical AI considerations, and post-deployment monitoring. Required Skills & Qualifications Bachelor’s/Master’s in Computer Science, Artificial Intelligence, Data Science, or a related field. 3–8 years of hands-on experience in AI/ML, including production model deployment. Advanced Python skills and deep expertise in libraries such as TensorFlow, PyTorch, Hugging Face, and Scikit-learn. Proven experience in deploying models to production (REST APIs, containers, cloud ML services). Deep understanding of ML algorithms, optimization, statistical modeling, and deep learning. Familiarity with tools like MLflow, Docker, Kubernetes, Airflow, and CI/CD pipelines for ML. Experience with cloud AI/ML services (AWS SageMaker, GCP Vertex AI, or Azure ML). Preferred Skills Hands-on with LLMs and GenAI tools (OpenAI, LangChain, RAG architecture, vector DBs). Experience in NLP, computer vision, or recommendation systems at scale. Knowledge of model explainability (SHAP, LIME), bias detection, and AI ethics. Strong understanding of software engineering best practices, microservices, and API architecture. What We Offer ✅ Leadership role in cutting-edge AI product development ✅ Influence on AI strategy and technical roadmap ✅ Exposure to enterprise and global AI projects ✅ Fast-paced, growth-focused work environment ✅ Flexible work hours, supportive leadership, and a collaborative team Apply now by sending your resume to: careers@asmadiya.com

Line of Service Advisory Industry/Sector Not Applicable Specialism SAP Management Level Senior Manager Job Description & Summary At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives. As a SAP consulting generalist at PwC, you will focus on providing consulting services across various SAP applications to clients, analysing their needs, implementing software solutions, and offering training and support for effective utilisation of SAP applications. Your versatile knowledge will allow you to assist clients in optimising operational efficiency and achieving their strategic objectives. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations Job Description & Summary: A career within…. Responsibilities: AI Architecture & Development · Design and implement generative AI models (e.g., Transformers, GANs, VAEs, Diffusion Models). · Architect Retrieval-Augmented Generation (RAG) systems and multi-agent frameworks. · Fine-tune pre-trained models for domain-specific tasks (e.g., NLP, vision, genomics). · Ensure model scalability, performance, and interpretability. System Integration & Deployment · Integrate AI models into full-stack applications using modern frameworks (React, Node.js, Django). · Deploy models using cloud platforms (AWS SageMaker, Azure ML, GCP Vertex AI). · Implement CI/CD pipelines and containerization (Docker, Kubernetes). Collaboration & Leadership · Work with data scientists, engineers, and domain experts to translate business/scientific needs into AI solutions. · Lead architectural decisions across model lifecycle: training, deployment, monitoring, and versioning. · Provide technical mentorship and guidance to junior team members. Compliance & Documentation · Ensure compliance with data privacy standards (HIPAA, GDPR). · Maintain comprehensive documentation for models, systems, and workflows. - Required Qualifications: · Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field. · 5+ years in AI/ML development; 3+ years in architecture or technical leadership roles. · Proficiency in Python, JavaScript, and frameworks like TensorFlow, PyTorch. · Experience with cloud platforms (AWS, Azure, GCP) and DevOps tools. · Strong understanding of NLP, computer vision, or life sciences applications. - Preferred Qualifications: · Experience in domains like marketing, capital markets, or life sciences (e.g., drug discovery, genomics). · Familiarity with Salesforce Einstein and other enterprise AI tools. · Knowledge of regulatory standards (FDA, EMA) and ethical AI practices. · Experience with multimodal data (text, image, genomic, clinical). Mandatory skill sets: Gen AI Architect Preferred skill sets: Gen AI Years of experience required: 10+yrs Education qualification: Btech MBA MCA MTECH Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Business Administration, Chartered Accountant Diploma, Bachelor of Engineering, Master of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills SAP Gen AI Hub Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Application Software, Business Model Development, Business Process Modeling, Business Systems, Coaching and Feedback, Communication, Creativity, Developing Training Materials, Embracing Change, Emerging Technologies, Emotional Regulation, Empathy, Enterprise Integration, Enterprise Software, Implementation Research, Implementation Support, Implementing Technology, Inclusion, Influence, Innovative Design, Intellectual Curiosity {+ 26 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

Education AI / ML Engineer - Required Skills & Qualifications: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or related field Technical Skills Proficient in Python and ML libraries: scikit-learn, XGBoost, pandas, NumPy, matplotlib, seaborn, etc. Strong understanding of machine learning algorithms and deep learning architectures (CNNs, RNNs, Transformers, etc.) Hands-on with TensorFlow , PyTorch , or Keras Experience in data preprocessing , feature selection , EDA , and model interpretability Comfortable with API development and deploying models using Flask, FastAPI, or similar Experience with MLOps tools like MLflow , Kubeflow , DVC , Airflow , etc. Familiarity with cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML Strong understanding of version control (Git), CI/CD, and containerization (Docker) Bonus Skills (Good To Have) NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers) Computer Vision experience using OpenCV or YOLO/Detectron Knowledge of Reinforcement Learning or Generative AI (GANs, LLMs) Experience with vector databases (e.g., Pinecone, Weaviate) and LangChain for AI agent building Familiarity with data labeling platforms and annotation workflows Soft Skills Analytical mindset with problem-solving skills Strong communication and collaboration abilities Ability to work independently in a fast-paced, agile environment Passion for AI/ML and eagerness to stay updated with the latest developments Skills: fastapi,pandas,ml libraries,pinecone,docker,langchain,matplotlib,yolo,numpy,yolo/detectron,nltk,machine learning,spacy,vertex ai,feature selection,lambda,gans,tensorflow,airflow,weaviate,data labeling,nlp frameworks,seaborn,python,git,ai,cnns,xgboost,model interpretability,deep learning architectures,dvc,generative ai,opencv,s3,detectron,aws,data preprocessing,api development,ci/cd,gcp,scikit-learn,transformers,vector databases,mlops tools,mlflow,sagemaker,machine learning algorithms,hugging face transformers,kubeflow,eda,annotation workflows,llms,containerization,reinforcement learning,ml,pytorch,flask,rnns,azure ml,keras

Job Title: AI/ML engineer Location: Gurgaon Hybrid Experience: 4–9 Years Job Type: [Full-time ] Job Summary: We are seeking a highly skilled and motivated AI/ML Engineer with strong AWS Cloud experience to join our data science and engineering team. The ideal candidate will design, build, and deploy scalable machine learning models and solutions while leveraging AWS services to manage infrastructure and model workflows. Key Responsibilities: Design, develop, and deploy machine learning models for predictive analytics, classification, NLP, or computer vision tasks. Use AWS services like SageMaker, S3, Lambda, Glue, EC2, EKS, and Step Functions for ML workflows and deployments. Preprocess and analyze large datasets for training and inference. Build scalable data pipelines and automate model training and evaluation. Collaborate with data engineers, scientists, and DevOps teams to productionize models. Optimize models for performance, interpretability, and scalability. Implement MLOps best practices (versioning, monitoring, model retraining pipelines). Conduct A/B testing and model performance tuning. Key Skills and Qualifications: Technical Skills: Strong proficiency in Python (including pandas, NumPy, Scikit-learn, etc.) Solid understanding of ML algorithms (regression, classification, clustering, deep learning) Experience with TensorFlow, PyTorch, or Keras Hands-on experience with AWS cloud services : SageMaker , S3 , Glue , Lambda , Step Functions , CloudWatch , IAM , etc. Experience with MLOps tools : MLflow, Docker, Git, CI/CD pipelines Knowledge of data pipeline frameworks (Airflow, AWS Glue, etc.) Familiarity with SQL and data wrangling in distributed environments (e.g., Spark) Nice to Have: Experience with NLP, LLMs, or Computer Vision Exposure to Big Data technologies (Kafka, Hadoop, etc.) Familiarity with API development using Flask or FastAPI Knowledge of Kubernetes for model container orchestration Educational Qualifications: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or related field.

Location: Hyderabad Department: Advanced AI Research & Engineering Reports To: Chief Technology Officer / Head of AI Strategy Employment Type: Full-time | Leadership Track Executive Summary: We are looking for a visionary and deeply experienced Artificial Intelligence Specialist to lead the design, architecture, and deployment of next-generation AI systems that will redefine our digital future. This role is reserved for an AI leader with demonstrated expertise in designing scalable, production-grade AI ecosystems; a deep understanding of neural architectures; and a track record of solving real-world complex challenges through intelligent automation, generative models, and predictive intelligence. This is not a conventional role—you will architect the AI backbone of future enterprise intelligence systems. Core Responsibilities: Architect and develop mission-critical AI models across domains: predictive analytics, generative AI, NLP, computer vision, and autonomous decision systems. Lead AI research-to-production workflows—from experimental design, data strategy, and model optimization to real-world deployment at scale. Design and refine advanced neural architectures , including transformers, LLMs, graph neural networks, and reinforcement learning agents. Spearhead multi-modal AI solutions integrating vision, voice, text, and time-series data streams. Collaborate with engineering, product, and C-suite teams to translate strategic business objectives into deployable AI solutions with measurable ROI. Guide data governance, ethical AI practices , explainability, compliance, and AI fairness protocols. Mentor a team of data scientists and machine learning engineers to deliver high-impact, production-ready AI pipelines. Continuously evaluate emerging AI tools, frameworks, and hardware acceleration techniques to maintain technological leadership . Represent the organization at AI conferences, forums, and research partnerships . Required Expertise: 10+ years of deep, hands-on experience in Artificial Intelligence, Machine Learning, and Applied Data Science. Master's or Ph.D. in AI/ML, Computer Science, Mathematics, Physics, or a related field (Ph.D. strongly preferred). Expertise in Python , along with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Scikit-learn . Demonstrated experience building and deploying LLMs, GANs, CNNs, RNNs, RL agents , and large-scale vector search systems. Deep knowledge of data engineering pipelines, model lifecycle management, and distributed computing . Advanced proficiency with MLOps, CI/CD for ML , containerization (Docker, Kubernetes), and versioned model deployment tools (MLflow, Kubeflow). Solid grounding in probability, statistics, optimization , and algorithmic design. Experience deploying AI on cloud infrastructure (AWS, GCP, Azure) and leveraging GPU/TPU environments. Preferred Edge (Not Mandatory but Advantageous): Experience working with Autonomous Systems, AI OS, Digital Twins , or AI-powered Operating Systems . Prior contributions to open-source AI libraries , patents, or published research in Tier-1 conferences (NeurIPS, ICML, CVPR, ACL). Domain specialization in healthcare AI, fintech AI, smart cities, or autonomous governance platforms . Hands-on experience with AI compliance frameworks (GDPR, HIPAA, model interpretability, and ethical AI) . What You’ll Get: Leadership opportunity in building core AI infrastructure for enterprise-scale and city-scale platforms. Access to state-of-the-art infrastructure , including AI supercomputing environments and high-volume data systems. Competitive salary package with equity options , bonuses, and leadership growth. Opportunity to shape the AI strategy of high-impact products reaching millions globally. Work culture that fosters innovation, autonomy, and research-driven engineering . Application & Interview Process: Please submit: Updated CV with detailed project accomplishments GitHub / Research portfolio Shortlisted candidates will be invited for: A technical deep-dive session Strategic AI system design challenge Panel interview with leadership and R&D teams This Role is Built For: AI pioneers who don’t just build models — they architect future intelligence ecosystems . If you live at the intersection of mathematics, machine learning, systems design, and innovation, we invite you to define the next generation of AI with us.

Please note that ARC Document Solutions is the hiring company and Inovact is the hiring partner for ARC. Position: AI Developer – Generative AI Location: Kolkata, India Company: ARC Document Solutions India Private Limited Website: www.e-arc.com About the role: We are seeking skilled AI Developers with expertise in Generative AI to join our growing team. The ideal candidate will have hands-on experience building applications powered by Large Language Models (LLMs), developing Retrieval-Augmented Generation (RAG) pipelines, and optimizing Chain of Thought (CoT) reasoning. You will play a key role in designing, developing, and deploying advanced AI solutions that integrate cutting-edge NLP techniques with scalable, production-ready systems. Key Responsibilities: AI Model Development Design and develop applications using Generative AI models. Implement RAG pipelines to enhance model accuracy by incorporating external knowledge sources. Apply CoT reasoning techniques to improve complex problem-solving capabilities. Prompt Engineering & Fine-Tuning Craft and optimize prompts for accurate, contextually relevant model outputs. Fine-tune LLMs with domain-specific data to improve performance and relevance. Vector Database & Indexing Integrate and optimize vector databases (e.g., Pinecone, FAISS, Milvus) for efficient data retrieval. Utilize frameworks like LangChain and LlamaIndex to build and query document embeddings. Model Optimization & Deployment Enhance model performance through hyperparameter tuning and experimentation. Deploy and monitor AI models in production environments, ensuring scalability, reliability, and robustness. Collaboration & Innovation Work closely with data scientists, engineers, and business teams to align AI solutions with business objectives. Stay up to date with the latest advancements in Generative AI, NLP, and ML technologies. Required Skills: Experience: 3+ years of experience in AI/ML development, with a strong focus on Generative AI and NLP. Technical Skills: Advanced proficiency in Python and AI libraries such as TensorFlow, PyTorch, and Keras. Hands-on expertise in RAG pipelines, CoT reasoning, and vector search. Strong knowledge of LangChain, LlamaIndex, and vector database integration. NLP Expertise: Deep understanding of transformers, BERT, GPT, and Named Entity Recognition (NER). Proven experience in fine-tuning LLMs and building custom NLP pipelines. Tools & Technologies: Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment. Experience with Docker, Kubernetes, and MLOps practices. Soft Skills: Strong analytical and problem-solving abilities. Excellent collaboration and communication skills. Preferred Skills: Experience with multi-modal AI models (text, image, audio). Knowledge of LLM evaluation frameworks and interpretability techniques. Familiarity with CI/CD pipelines for AI model deployment.

India ID asp-006-0725 Full Time 07/07/2025 Job Overview: We are seeking an experienced and visionary Technical Lead – Data Science to lead and drive AI/ML solution delivery across complex and large-scale business problems. The ideal candidate will have deep hands-on expertise in AI, Machine Learning, Deep Learning, NLP, and Generative AI (Gen AI), coupled with a strong leadership mindset to mentor teams, architect scalable solutions, and influence key stakeholders. Key Responsibilities: Lead the architecture, development, and deployment of advanced AI/ML/NLP/Gen AI models and solutions. Work closely with business stakeholders to understand use cases, translate them into technical solutions, and drive end-to-end implementation. Design and build scalable and production-grade machine learning systems, ensuring high performance, reliability, and efficiency. Apply Natural Language Processing (NLP) and Generative AI (LLMs, transformers, prompt engineering) for innovative and high-impact business applications. Mentor and lead a team of data scientists and ML engineers, ensuring code quality, knowledge sharing, and best practice adoption. Drive technical decision-making, model governance, risk mitigation, and continuous improvement. Collaborate with cross-functional teams across data engineering, product, and DevOps to ensure seamless integration and delivery. Required Skills: Strong programming skills in Python and experience with key libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers. Deep expertise in Machine Learning, NLP, and Generative AI, with proven success in implementing real-world solutions. Hands-on experience with cloud platforms like AWS, Azure, or GCP for model training, deployment, and scaling. Solid understanding of data structures, algorithms, and MLOps practices. Experience in leading medium to large AI/ML teams and delivering high-visibility projects. Strong communication and stakeholder management skills, with the ability to influence and present to senior leadership. Preferred Skills: Exposure to end-to-end ML lifecycle including data prep, model monitoring, CI/CD pipelines, and model interpretability tools. Experience in product-oriented or consulting organizations is a plus. Certifications in AI/ML or cloud technologies (AWS/GCP/Azure) are advantageous.

Company Description Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. Job Description Payments has become a very active hot area in the last couple of years, creating a strong demand for innovation. This will be a very exciting area in the next 5 to 10 years. Not only is VISA a leader in the payment industry and has been for a long time, but it is also quickly transitioning into a technology company that is fostering an environment for applying the latest technology to solve exciting problems in this area. Visa AI as a Service,AIaS operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, AIaS automates the updates to data, models, and applications. Combined with strong AI governance, AIaS optimizes the performance, scalability, interpretability and reliability of AI models and services. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you! This position is for a Senior Manager in Data Engineering with solid development experience who will focus on creating new capabilities for AI as a Service while maturing our code base and development processes. In this position, you are first a passionate and talented developer that can work in a dynamic environment as a member of Agile Scrum teams. Your strong technical leadership, problem-solving abilities, coding, testing and debugging skills is just a start. You must be dedicated to filling product backlog and delivering production ready code. You must be willing to go beyond the routine and prepared to do a little bit of everything. You will be an integral part of the development team, sometimes investigating new requirements and design and at times refactoring existing functionality for performance and maintainability, but always working on ways to make us more efficient and provide better solutions to our end customers. The role is for a self organized individual with knowledge of web application and web service development. The candidate will perform hands-on activities including design, documentation, development and test of new functionality. Candidate must be flexible and willing to switch tasks based on team’s needs. This position will be based in Bangalore, India. If this sounds exciting, we want to chat and tell you more about our work culture and environment and see if this will be a good fit for both of us. Essential Functions Collaborate with project teams, data science teams and development teams to drive the technical roadmap and guide development and implementation of new data driven business solutions. Drive technical standard and best practices, and continuously improve AI Platform engineering scalability. Architecture and design of AI Platform services including Machine Learning Engines, In Memory Computing Systems, Streaming Computing Systems, Distributed Data Systems and etc., in Golang, Java, and Python. Coordinate the implementation among development teams to ensure system performance, security, scalability and availability. Coaching and mentoring junior team members and evolving team talent pipeline. This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. Preferred Qualifications: 8+ years of relevant work experience and a Bachelors degree, OR 11+ years of relevant work experience 5 years or more of experience in leading development teams Proven knowledge of successful design, architecture and development using Big Data Hadoop, J2EE and Spark with large data volumes and transaction systems Possesses a deep understanding of benefits or drawbacks of different integration patterns Experience with GIT,Stash, Maven and Jenkins Experience in MySQL, Redis DB or Elastic Search on Unix or Linux platform Ability to solve complex software development, design issues Ability to write clean, coherent code following established coding guidelines Strong interpersonal, facilitation, and effective communication skills both written and verbal and the ability to present complex ideas in a clear, concise way Experience developing as part of Agile or Scrum team is preferred Passionate about delivering zero defect code that meet or exceed the proposed defect SLA and have high sense of accountability for quality and timeliness of deliverables Ability to deliver on multiple projects and manage priorities based on changing directions Highly driven, resourceful and results oriented Demonstrated ability to lead and navigate through ambiguity Past experience in Payments knowledge is preferred Additional Information Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

AI Research Intern – AryaXAI AI Alignment Labs Commitment: Full-time internship (6 months; potential extension or full-time offer) Start Date: Rolling About AryaXAI AI Alignment Labs AryaXAI AI Alignment Labs, based out of Mumbai, India and Paris, France, is the alignment and explainability division of AryaXAI.com, part of Aurionpro Solutions. We work on AI interpretability and trustworthiness for mission-critical sectors. Our open-source initiatives include the xai_evals benchmarking suite and the DLBacktrace explainability framework, both designed to make AI more transparent, reliable, and aligned with human values. What You’ll Do Collaborate closely with our research and engineering teams on one of the areas: Library Development: Architect and enhance open-source Python tooling for alignment, explainability, uncertainty quantification, robustness, and machine unlearning. Model Benchmarking: Conduct rigorous evaluations of LLMs and deep networks under domain shifts, adversarial conditions, and regulatory constraints. Explainability & Trust: Design and implement XAI techniques (LRP, SHAP, Grad-CAM, Backtrace) across text, image, and tabular modalities. Mechanistic Interpretability: Probe internal model representations and circuits—using activation patching, feature visualization, and related methods—to diagnose failure modes and emergent behaviors. Uncertainty & Risk: Develop, implement, and benchmark uncertainty estimation methods (Bayesian approaches, ensembles, test-time augmentation) alongside robustness metrics for foundation models. Research Contributions: Author and maintain experiment code, run systematic studies, and co-author whitepapers or conference submissions. General Required Qualifications Strong Python expertise: writing clean, modular, and testable code. Theoretical foundations: deep understanding of machine learning and deep learning principles with hands-on experience with PyTorch. Transformer architectures & fundamentals: comprehensive knowledge of attention mechanisms, positional encodings, tokenization and training objectives in BERT, GPT, LLaMA, T5, MOE, Mamba, etc. Version control & CI/CD: Git workflows, packaging, documentation, and collaborative development practices. Collaborative mindset: excellent communication, peer code reviews, and agile teamwork. Preferred Domain Expertise (Any one of these is good) : Explainability: applied experience with XAI methods such as SHAP, LIME, IG, LRP, DL-Bactrace or Grad-CAM. Mechanistic interpretability: familiarity with circuit analysis, activation patching, and feature visualization for neural network introspection. Uncertainty estimation: hands-on with Bayesian techniques, ensembles, or test-time augmentation. Quantization & pruning: applying model compression to optimize size, latency, and memory footprint. LLM Alignment techniques: crafting and evaluating few-shot, zero-shot, and chain-of-thought prompts; experience with RLHF workflows, reward modeling, and human-in-the-loop fine-tuning. Post-training adaptation & fine-tuning: practical work with full-model fine-tuning and parameter-efficient methods (LoRA, adapters), instruction tuning, knowledge distillation, and domain-specialization. Additional Experience (Nice-to-Have) Publications: contributions to CVPR, ICLR, ICML, KDD, WWW, WACV, NeurIPS, ACL, NAACL, EMNLP, IJCAI or equivalent research experience. Open-source contributions: prior work on AI/ML libraries or tooling. Domain exposure: risk-sensitive applications in finance, healthcare, or similar fields. Performance optimization: familiarity with large-scale training infrastructures. What We Offer Real-world impact: address high-stakes AI challenges in regulated industries. Compute resources: access to GPUs, cloud credits, and proprietary models. Competitive stipend: with potential for full-time conversion. Authorship opportunities: co-authorship on papers, technical reports, and conference submissions.

Company Overview : At Growth Loops Technology, we are at the forefront of AI innovation, leveraging cutting-edge machine learning and natural language processing (NLP) techniques to build transformative products. We are looking for an experienced and passionate LLM Engineer to join our team and help us develop and optimize state-of-the-art language models that push the boundaries of what's possible with AI. Job Description : As an LLM Engineer, you will be responsible for designing, building, and fine-tuning large-scale language models (LLMs) to solve complex real-world problems. You will work alongside data scientists, machine learning engineers, and product teams to ensure our models are not only accurate but also efficient, scalable, and capable of handling diverse use cases. The ideal candidate will have a strong background in natural language processing, deep learning, and large-scale distributed systems. You should be passionate about advancing the field of AI and have hands-on experience with LLMs, such as GPT, BERT, or similar architectures. Key Responsibilities : Model Development : Design, develop, and fine-tune large language models (LLMs) for various applications, including text generation, translation, summarization, and question answering. Research & Innovation : Stay up to date with the latest advancements in NLP and LLM architectures, and propose new approaches to improve model performance and efficiency. Optimization : Implement optimization techniques to reduce computational resource requirements and improve model inference speed without sacrificing accuracy or performance. Scalability : Develop strategies for training and deploying models at scale, ensuring robustness and reliability in production environments. Collaboration : Work closely with cross-functional teams (data science, software engineering, product) to integrate LLM capabilities into our products and solutions. Evaluation & Benchmarking : Establish and maintain rigorous testing, validation, and benchmarking procedures to assess model quality, performance, and generalization. Model Explainability : Develop methods to improve the interpretability and explainability of language models, ensuring that outputs can be understood and trusted by end-users. Qualifications : Education : Bachelor's, Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience : Proven experience (1+ years) working with NLP, deep learning, and LLM architectures (e.g., GPT, BERT, T5, etc.). Expertise in programming languages such as Python and experience with machine learning frameworks like TensorFlow, PyTorch, or JAX. Solid understanding of transformer models, attention mechanisms, and the architecture of large-scale neural networks. Experience with distributed computing, GPU acceleration, and cloud-based machine learning platforms (e.g., AWS, GCP, Azure). Familiarity with model deployment tools and practices (e.g., TensorFlow Serving, or Hugging Face). Skills : Strong problem-solving skills and ability to work on complex, ambiguous tasks. Solid understanding of model evaluation metrics for NLP tasks. Experience with large datasets and parallel computing for training and fine-tuning LLMs. Familiarity with optimization techniques such as pruning, quantization, or knowledge distillation. Excellent communication skills, both written and verbal, with the ability to explain complex technical concepts to non-technical stakeholders. Nice to Have : Experience with reinforcement learning or few-shot learning in the context of language models. Contributions to open-source projects or publications in top-tier AI/ML conferences (e.g., NeurIPS, ACL, ICML). What We Offer : Competitive salary and benefits package Flexible work schedule with remote work options Opportunity to work on cutting-edge AI technology with a passionate team A collaborative and inclusive work culture focused on innovation

AI Research Intern – AryaXAI AI Alignment Labs Location: Remote / Mumbai, India Commitment: Full-time internship (6 months; potential extension or full-time offer) Start Date: Rolling About AryaXAI AI Alignment Labs AryaXAI AI Alignment Labs, based out of Mumbai, India and Paris, France, is the alignment and explainability division of AryaXAI.com , part of Aurionpro Solutions. We work on AI interpretability and trustworthiness for mission-critical sectors. Our open-source initiatives include the xai_evals benchmarking suite and the DLBacktrace explainability framework, both designed to make AI more transparent, reliable, and aligned with human values. What You’ll Do Collaborate closely with our research and engineering teams on one of the areas: Library Development: Architect and enhance open-source Python tooling for alignment, explainability, uncertainty quantification, robustness, and machine unlearning. Model Benchmarking: Conduct rigorous evaluations of LLMs and deep networks under domain shifts, adversarial conditions, and regulatory constraints. Explainability & Trust: Design and implement XAI techniques (LRP, SHAP, Grad-CAM, Backtrace) across text, image, and tabular modalities. Mechanistic Interpretability: Probe internal model representations and circuits—using activation patching, feature visualization, and related methods—to diagnose failure modes and emergent behaviors. Uncertainty & Risk: Develop, implement, and benchmark uncertainty estimation methods (Bayesian approaches, ensembles, test-time augmentation) alongside robustness metrics for foundation models. Research Contributions: Author and maintain experiment code, run systematic studies, and co-author whitepapers or conference submissions. General Required Qualifications Strong Python expertise: writing clean, modular, and testable code. Theoretical foundations: deep understanding of machine learning and deep learning principles with hands-on experience with PyTorch. Transformer architectures & fundamentals: comprehensive knowledge of attention mechanisms, positional encodings, tokenization and training objectives in BERT, GPT, LLaMA, T5, MOE, Mamba, etc. Version control & CI/CD: Git workflows, packaging, documentation, and collaborative development practices. Collaborative mindset: excellent communication, peer code reviews, and agile teamwork. Preferred Domain Expertise (Any one of these is good) : Explainability: applied experience with XAI methods such as SHAP, LIME, IG, LRP, DL-Bactrace or Grad-CAM. Mechanistic interpretability: familiarity with circuit analysis, activation patching, and feature visualization for neural network introspection. Uncertainty estimation: hands-on with Bayesian techniques, ensembles, or test-time augmentation. Quantization & pruning: applying model compression to optimize size, latency, and memory footprint. LLM Alignment techniques: crafting and evaluating few-shot, zero-shot, and chain-of-thought prompts; experience with RLHF workflows, reward modeling, and human-in-the-loop fine-tuning. Post-training adaptation & fine-tuning: practical work with full-model fine-tuning and parameter-efficient methods (LoRA, adapters), instruction tuning, knowledge distillation, and domain-specialization. Additional Experience (Nice-to-Have) Publications: contributions to CVPR, ICLR, ICML, KDD, WWW, WACV, NeurIPS, ACL, NAACL, EMNLP, IJCAI or equivalent research experience. Open-source contributions: prior work on AI/ML libraries or tooling. Domain exposure: risk-sensitive applications in finance, healthcare, or similar fields. Performance optimization: familiarity with large-scale training infrastructures. What We Offer Real-world impact: address high-stakes AI challenges in regulated industries. Compute resources: access to GPUs, cloud credits, and proprietary models. Competitive stipend: with potential for full-time conversion. Authorship opportunities: co-authorship on papers, technical reports, and conference submissions.

Position : Environmental Data Scientist Salary: upto ₹50000 pm Location: Ahmedabad [Only preferring candidates from Gujarat] Experience: 2+ Years we are seeking a research-driven Environmental Data Scientist to lead the development of advanced algorithms that enhance the accuracy, reliability, and performance of air quality sensor data. This role goes beyond traditional data science — it focuses on solving real-world challenges in environmental sensing, such as sensor drift, cross-interference, and data anomalies. Key Responsibilities: Design and implement algorithms to improve the accuracy, stability, and interpretability of air quality sensor data (e.g., calibration, anomaly detection, cross-interference mitigation, and signal correction) Conduct in-depth research on sensor behavior and environmental impact to inform algorithm development Collaborate with software and embedded systems teams to integrate these algorithms into cloud or edge-based systems Analyze large, complex environmental datasets using Python, R, or similar tools Continuously validate algorithm performance using lab and field data; iterate for improvement Develop tools and dashboards to visualize sensor behavior and algorithm impact Assist in environmental research projects with statistical analysis and data interpretation Document algorithm design, testing procedures, and research findings for internal use and knowledge sharing Support team members with data-driven insights and code-level contributions as needed Assist other team members with writing efficient code and overcoming programming challenges Education/Experience Required Skills & Qualifications Bachelor’s or Master’s degree in one of the following fields: Environmental Engineering / Science, Chemical Engineering, Electronics / Instrumentation Engineering, Computer Science / Data Science, Physics / Atmospheric Science (with data or sensing background) 1-2 years of hands-on experience working with sensor data or IoT-based environmental monitoring systems Strong knowledge of algorithm development, signal processing, and statistical analysis Proficiency in Python (pandas, NumPy, scikit-learn, etc.) or R, with experience handling real-world sensor datasets Ability to design and deploy models in a cloud or embedded environment. Excellent problem-solving and communication skills. Passion for environmental sustainability and clean-tech. Preferred Qualifications: Familiarity with time-series anomaly detection, sensor fusion, signal noise reduction techniques or geospatial data processing. Exposure to air quality sensor technologies, environmental sensor datasets, or dispersion modeling. For Quick Response, please fill out this fo rm https://docs.google.com/forms/d/e/1FAIpQLSeBy7r7b48Yrqz4Ap6-2g_O7BuhIjPhcj-5_3ClsRAkYrQtiA/viewform?usp=sharing&ouid=106739769571157586077

Job Summary We are seeking a highly skilled and experienced AI/ML Subject Matter Expert (SME) to lead the design, development, and deployment of cutting-edge machine learning and artificial intelligence solutions. The ideal candidate will possess deep technical expertise, a strong research background, and a proven ability to translate complex business problems into intelligent, scalable models and systems. Key Responsibilities Serve as the primary expert on AI/ML technologies, frameworks, and best practices across internal teams or client engagements. Design, develop, train, test, and deploy machine learning models, including supervised, unsupervised, and reinforcement learning. Collaborate with data scientists, engineers, and product teams to deliver end-to-end AI/ML solutions. Provide strategic direction on AI adoption, model interpretability, and responsible AI practices. Evaluate and select appropriate algorithms, tools, and technologies based on business and technical requirements. Stay abreast of AI/ML research and industry trends; lead the adoption of emerging techniques like LLMs, generative AI, or federated learning. Present complex AI/ML concepts and project outcomes to non-technical stakeholders and executives. Mentor junior team members and contribute to talent development and technical leadership within the team. Qualifications Required: Master’s or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. 5+ years of experience in AI/ML solution design and implementation. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong knowledge of model development lifecycle, including data preprocessing, feature engineering, and model validation. Experience with cloud platforms (AWS, Azure, GCP) and ML Ops pipelines. Strong analytical and problem-solving skills with experience applying AI to real-world problems. Thanks & Regards Prashant Awasthi Vastika 9711189829

Job description Core Responsibilities Project Leadership: Own the end-to-end lifecycle of AI/ML projects—from scoping and prototyping to deployment and monitoring. Team Management: Lead, mentor, and grow a team of ML engineers, data scientists, and researchers. Model Development: Design, train, and evaluate machine learning and deep learning models for predictive analytics, NLP, CV, recommendation systems, etc. MLOps: Oversee model deployment, versioning, monitoring, and continuous training in production environments. Cross-Functional Collaboration: Work closely with data engineers, software developers, product managers, and business stakeholders. Research & Innovation: Evaluate cutting-edge AI/ML research and integrate suitable technologies into company products and platforms. Compliance & Ethics: Ensure responsible AI practices, addressing fairness, bias, interpretability, and compliance requirements. Technical Skills Programming: Expert in Python (NumPy, pandas, scikit-learn), and familiar with C++, R, or Java if needed. Frameworks: TensorFlow, PyTorch, Keras, Hugging Face Transformers. Data Tools: SQL, Spark, Kafka, Airflow. Cloud & DevOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, SageMaker, Vertex AI. Techniques: Supervised/unsupervised learning, deep learning, NLP, computer vision, reinforcement learning. MLOps: CI/CD for ML, monitoring (Prometheus, Grafana), feature stores, model drift detection. Typical Background 5+ years experience in AI/ML development. 2+ years in a leadership or team lead role. Job Type: Full-time Benefits: Provident Fund Location Type: In-person Schedule: Day shift Monday to Friday Morning shift Work Location: In person Speak with the employer +91 8146237069 Application Deadline: 05/07/2025

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: Act as the senior software engineer RPA development using UiPath or Mulesoft Be able to develop, design and implement UiPath solutions Design and implement scalable ML solutions using state-of-the-art generative models Fine-tune and optimize large language models (LLMs) for domain-specific applications Collaborate with cross-functional teams to integrate RPA/AI capabilities into products and services Develop pipelines for data preprocessing, model training, evaluation, and deployment Ensure model performance, fairness, and interpretability through rigorous testing and validation Act as a mentor to other technical team members providing guidance and possible solution approaches Be able to engage with the business and gather requirements and organize them utilizing an Agile based approach Serve as the technical subject matter expert for the development team and work closely with all the global development team to lead, enhance, and maintain the application Participate in scrum meetings and relay business and technical decisions to the development team Work closely with the product owner and business SMEs on design of product Coordinate release planning Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Engineering degree or equivalent experience 7+ years of hands-on experience in both frontend and backend development tasks, working with technologies such as UiPath and related frameworks 2+ years of experience in AI/ML engineering, focused on Generative AI or Agentic AI 2+ years of hands-on experience working with Microsoft Azure Cloud Hands-on experience with LLMs, prompt engineering, and fine-tuning techniques MS Azure, Rally experience Experience working in agile methodology Experience driving UiPath solutions and it’s framework, also guiding a team to realizing those solutions Significant experience in UiPath development design and architecture Experience mentoring other software engineers Experience serving as senior engineer being able to collaborate with the product owner in documenting feature and user story acceptance criteria; understand how the features will integrate into the current application as well At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.