1558 Sagemaker Jobs - Page 34

What you’ll do Own the full stack Architect, implement, and maintain backend services in Python/Django and modern frontend SPAs in React (or Vue/Svelte/Next) . Lead and mentor Establish engineering best practices, conduct code reviews, and (as we grow) onboard and coach junior developers or contractors. Ship green‑field GenAI products Prototype and productionize RAG pipelines using Haystack, LangChain, LlamaIndex , vector databases, and orchestration tools. Collaborate directly with clients Translate ambiguous business problems into technical roadmaps; present progress and trade‑offs to executive and non‑technical audiences. Automate & scale Design CI/CD, infrastructure‑as‑code, containerization, monitoring, and observability for cloud deployments (AWS/GCP/Azure—your call). Champion quality & security Implement testing strategies (unit, integration, e2e), enforce secure‑by‑default coding, and manage data privacy throughout the ML lifecycle. You are Seasoned: 3 + years professional experience with Django and 3 + years with a modern JavaScript/TypeScript framework (React preferred). Polyglot & pragmatic: fluent in SQL, REST/GraphQL, Git workflows, containerization, and cloud services. GenAI‑curious (or better): hands‑on with Haystack, LangChain, LlamaIndex, or equivalent frameworks for building LLM apps. Product‑minded: thrive in early‑stage ambiguity, turning sketches or paragraphs into shippable software. Communicative: write crisp design docs and explain complex ideas without jargon. Self‑directed & reliable: comfortable working solo across time zones, setting realistic estimates, and delivering on them. Bonus points for Production experience with vector databases (Pinecone, Qdrant, pgvector, etc.). DevOps chops (Terraform, Pulumi, GitHub Actions, Argo). MLOps experience (Vertex AI, SageMaker, BentoML, Weights & Biases). UI/UX sensitivity or data‑viz expertise. Prior startup or consultancy background. What we offer Remote‑first flexibility – Hybrid work from centrally located office space Travel + Food Compensation: For in-office days Competitive salary + meaningful equity – grow with the company you’re building. Impact from day one – zero red tape, direct access to founders & clients, and a roadmap you help define the product. The hiring process Intro call (30 min) – culture & high‑level skill alignment. Technical deep dive (75 min) – system‑design discussion + lightweight coding exercise. Portfolio review (45 min) – walk us through a past project you’re proud of. Founder chat (30 min) – values alignment & offer discussion.

Job Description As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions. Job Responsibilities Establish and promote a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates. Lead efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization. Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques. Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines Advise on the strategy and development of multiple products, applications, and technologies. Lead advisor on the technical feasibility and business need for AIML use cases. Liaise with firm wide AI ML stakeholders. Translate highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well informed decisions about technology advancements. Influence across business, product and technology teams and successfully manages senior stakeholder relationships. champion the firm's culture of diversity, opportunity, inclusion, and respect. Required Qualifications, Capabilities, And Skills Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise MS and/or PhD in Computer Science, Machine Learning, or a related field At least 10 years’ experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must. Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team. Good understanding in deep learning frameworks such as PyTorch or TensorFlow. Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search). Ability to work on system design from ideation through completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners. Practical cloud native experience such as AWS needed. Preferred Qualifications, Capabilities, And Skills Experience with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Advanced knowledge in Reinforcement Learning or Meta Learning. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale. Responsibilities: Leadership & Management Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment; Drive the roadmap for machine learning projects aligned with business goals; Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery. Machine Learning & LLM Expertise Design, develop, and fine-tune LLMs and other machine learning models to solve business problems; Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction; Stay ahead of advancements in LLMs and apply emerging technologies; Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML. AWS Cloud Expertise Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.); Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS; Ensure best practices in security, monitoring, and compliance within the cloud infrastructure. Technical Execution Oversee the entire ML lifecycle, from research and experimentation to production and maintenance; Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows; Debug, troubleshoot, and optimize production ML models for performance. Team Development & Communication Conduct regular code reviews and ensure engineering standards are upheld; Facilitate professional growth and learning for the team through continuous feedback and guidance; Communicate progress, challenges, and solutions to stakeholders and senior leadership. Qualifications: Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models); Strong expertise in AWS Cloud Services; Strong experience in ML/AI, including at least 2 years in a leadership role; Hands-on experience with Python, TensorFlow/PyTorch, and model optimization; Familiarity with MLOps tools and best practices; Excellent problem-solving and decision-making abilities; Strong communication skills and the ability to lead cross-functional teams; Passion for mentoring and developing engineers.

We are seeking an experienced and innovative Generative AI Developer to join our AWAC team. In this role, you will lead the design and development of GenAI and Agentic AI applications using state of the art LLMs and AWS native services. You will work on both R&D focused proofof concepts and production grade implementations, collaborating with cross-functional teams to bring intelligent, scalable solutions to life. Key Responsibilities Design, develop, and deploy Generative AI and Agentic AI applications using LLMs such as Claude, Cohere, Titan, and others. Lead the development of proof of concept (PoC) solutions to explore new use cases and validate AI driven innovations. Architect and implement retrieval augmented generation (RAG) pipelines using LangChain and Vector Databases like OpenSearch. Integrate with AWS services including Bedrock API, SageMaker, SageMaker JumpStart, Lambda, EKS/ECS, Amazon Connect, Amazon Q. Apply few shot, one shot, and zero shot learning techniques to fine tune and prompt LLMs effectively. Collaborate with data scientists, ML engineers, and business stakeholders to translate complex requirements into scalable AI solutions. Implement CI/CD pipelines, infrastructure as code using Terraform, and follow DevOps best practices. Optimize performance, cost, and reliability of AI applications in production environments. Document architecture, workflows, and best practices to support knowledge sharing and onboarding. Required Skills & Technologies Experience in Python development, with at least 2 years in AI/ML or GenAI projects. Strong hands on experience with LLMs and Generative AI frameworks. Proficiency in LangChain, Vector DBs (e.g OpenSearch), and prompt engineering. Deep understanding of AWS AI/ML ecosystem: Bedrock, SageMaker, Lambda, EKS/ECS. Experience with serverless architectures, containerization, and cloud native development. Familiarity with DevOps tools: Git, CI/CD, Terraform. Strong debugging, performance tuning, and problem solving skills. Preferred Qualifications Experience with Amazon Q, Amazon Connect, or Amazon Titan. Familiarity with Claude, Cohere, or other foundation models. Bachelors or Master s degree in Computer Science, AI/ML, or a related field. Experience in building agentic workflows and multi agent orchestration is a plus.

JOB DESCRIPTION As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions. Job responsibilities: Establish and promote a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates. Lead efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization. Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques. Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines Advise on the strategy and development of multiple products, applications, and technologies. Lead advisor on the technical feasibility and business need for AIML use cases. Liaise with firm wide AI ML stakeholders. Translate highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well informed decisions about technology advancements. Influence across business, product and technology teams and successfully manages senior stakeholder relationships. champion the firm's culture of diversity, opportunity, inclusion, and respect. Required qualifications, capabilities, and skills: Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise MS and/or PhD in Computer Science, Machine Learning, or a related field At least 10 years’ experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must. Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team. Good understanding in deep learning frameworks such as PyTorch or TensorFlow. Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search). Ability to work on system design from ideation through completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners. Practical cloud native experience such as AWS needed. Preferred qualifications, capabilities, and skills: Experience with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Advanced knowledge in Reinforcement Learning or Meta Learning. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. ABOUT THE TEAM J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

- Bachelor's degree in a quantitative field (e.g., Business, Economics, Statistics, Mathematics, Computer Science) or equivalent practical experience - Proficiency in Microsoft Excel and SQL skills - Experience with data analysis and creating visualizations - Knowledge of AI/ML tools and platforms (e.g., Amazon SageMaker, TensorFlow, Python libraries for data analysis) - Understanding of basic machine learning concepts and their business applications - Strong problem-solving and analytical skills - Excellent written and verbal communication skills - Ability to work effectively in a team environment At Amazon, we're working to be the most customer-centric company on Earth. To get there, we need talented, bright, and data-driven people. If you'd like to help us build the place to find and buy anything online, this is your chance to make history. Within Amazon’s Workplace Health & Safety team, ‘The Employee Safety Experience (ESE)’ team is seeking an analytical and detail-oriented candidate. This is an exciting opportunity to join a team in a huge growth area for Amazon. The vision of this team is to build an Amazon safety experience that is responsive to our employees needs and actionable by our leaders. One of the vertical of ESE is ‘The Business and Program Analysis’ team with focus on providing technical guidance and thought leadership on all ESE programs from ideation through execution. The ideal candidate will have a strong analytical mindset, attention to detail, and the ability to communicate complex information clearly and concisely. You should be comfortable working with data, have basic SQL skills, and be eager to learn and grow in a fast-paced environment. Key job responsibilities Key responsibilities include: • Provide analytics solutions to solve business problems • Extract available data and apply basic transformations using spreadsheets, SQL, and other relevant tools • Use descriptive analysis techniques to understand impact and identify drivers • Generate findings that inform team decisions by providing visibility to business performance, highlighting anomalies, and revealing new opportunities • Document your analytical approach, including metric definitions, applied logic, assumptions, and data sources • Work with technology teams to contribute towards development/ improvement of portals, dashboards and online tools including logic validation. • Share findings with your team through written and verbal communication channels • Learn and apply analytical best practices to improve team and process efficiency • Help train new peers and contribute to the development of your team 3+ years of working experience in a data analysis or business intelligence role Experience with business intelligence tools (e.g., Tableau, QuickSight) Exposure to generative AI tools and their applications in business analytics Strong attention to detail and ability to manage multiple priorities Demonstrated ability to learn quickly and adapt to new technologies and processes Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Design and lead the development of various artificial intelligence initiatives to help improve health and wellness of patients Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccer’s machine-learning algorithms and take them to market with partnerships with different organizations Proven ability to break down complex business problems into machine learning problems and design solution workflows. Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Stay updated on advancements in AI/ML technologies and apply them to enhance existing systems. Requirements Preferably Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 3+ years of experience in Data Science (healthcare experience will be a plus) Strong hands-on experience in Python - building enterprise applications. Deep experience in classical and new age NLP techniques - must have either trained or fine tuned a transformer architecture. Understanding new age fine LLM tuning techniques like PEFT [experience with LoRA and QLoRA preferred] Should have experience with GenAI tools and techniques including but not limited to RAG, VectorDBs, Agentic AI fundamentals. Proficiency in at least one of the the following - LangChain, Crew.AI Should have hands-on experience with deep learning frameworks. Pytorch HuggingFace transformers Hands on experience with at least one ML platform from amongst Databricks, Azure ML, Sagemaker Good to have - Hands on experience in API frameworks leveraging their capabilities for developing robust web applications. [Experience FastAPI preferred] Good to have - Comfortable with AWS cloud technologies Benefits Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Pet-Friendly Office*: Spend more time with your treasured friends, even when you're away from home. Bring your furry friends with you to the office and let your colleagues become their friends, too. *Noida office only Creche Facility for children*: Say goodbye to worries and hello to a convenient and reliable creche facility that puts your child's well-being first. *India offices Where and how we work Our Noida office is situated in a posh techspace, equipped with various amenities to support our work environment. Here, we follow a five-day work schedule, allowing us to efficiently carry out our tasks and collaborate effectively within our team. Innovaccer is an equal opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer: Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure— extending the human touch in healthcare. For more information, visit www.innovaccer.com.

Senior Gen AI Engineer Job Description Brightly Software is seeking an experienced candidate to join our Product team in the role of Gen AI engineer to drive best in class client-facing AI features by creating and delivering insights that advise client decisions tomorrow. As a Gen AI Engineer, you will play a critical role in building AI offerings for Brightly. You will partner with our various software Product teams to drive client facing insights to inform smarter decisions faster. This will include the following: Lead the evaluation and selection of foundation models and vector databases based on performance and business needs Design and implement applications powered by generative AI (e.g., LLMs, diffusion models), delivering contextual and actionable insights for clients. Establish best practices and documentation for prompt engineering, model fine-tuning, and evaluation to support cross-domain generative AI use cases. Build, test, and deploy generative AI applications using standard tools and frameworks for model inference, embeddings, vector stores, and orchestration pipelines. Key Responsibilities: Guide the design of multi-step RAG, agentic, or tool-augmented workflows Implement governance, safety layers, and responsible AI practices (e.g., guardrails, moderation, auditability) Mentor junior engineers and review GenAI design and implementation plans Drive experimentation, benchmarking, and continuous improvement of GenAI capabilities Collaborate with leadership to align GenAI initiatives with product and business strategy Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector stores like Pinecone, FAISS, or AWS Opensearch Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for model building. Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, natural language processing) with strong exerience in predictive and stastical modelling. Implement and deploy machine learning models into production using AWS services, with a strong focus on Amazon SageMaker (e.g., SageMaker Studio, training jobs, inference endpoints, SageMaker Pipelines). Understanding and development of state management workflows using Langraph. Develop GenAI applications using Hugging Face Transformers, LangChain, and Llama related frameworks Engineer and evaluate prompts, including prompt chaining and output quality assessment Apply NLP and transformer model expertise to solve language tasks Deploy GenAI models to cloud platforms (preferably AWS) using Docker and Kubernetes Monitor and optimize model and pipeline performance for scalability and efficiency Communicate techn

Gen AI Engineer Job Description Brightly Software is seeking a high performer to join our Product team in the role of Gen AI engineer to drive best in class client-facing AI features by creating and delivering insights that advise client decisions tomorrow. As a Gen AI Engineer, you will play a critical role in building AI offerings for Brightly. You will partner with our various software Product teams to drive client facing insights to inform smarter decisions faster. This will include the following: Design and implement applications powered by generative AI (e.g., LLMs, diffusion models), delivering contextual and actionable insights for clients. Establish best practices and documentation for prompt engineering, model fine-tuning, and evaluation to support cross-domain generative AI use cases. Build, test, and deploy generative AI applications using standard tools and frameworks for model inference, embeddings, vector stores, and orchestration pipelines. Key Responsibilities: Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector stores like Pinecone, FAISS, or AWS OpenSearch Develop GenAI applications using Hugging Face Transformers, LangChain, and Llama related frameworks Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for model building. Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, natural language processing) with strong exerience in predictive and stastical modelling. Implement and deploy machine learning models into production using AWS services, with a strong focus on Amazon SageMaker (e.g., SageMaker Studio, training jobs, inference endpoints, SageMaker Pipelines). Understanding and development of state management workflows using Langraph. Engineer and evaluate prompts, including prompt chaining and output quality assessment Apply NLP and transformer model expertise to solve language tasks Deploy GenAI models to cloud platforms (preferably AWS) using Docker and Kubernetes Monitor and optimize model and pipeline performance for scalability and efficiency Communicate technical concepts clearly to cross-functional and non-technical stakeholders Thrive in a fast-paced, lean environment and contribute to scalable GenAI system design Qualifications Bachelor’s degree is required 2-4 years of experience of total experience with a strong focus on AI and ML and 1+ years in core GenAI Engineering Demonstrated expertise in working with large language models (LLMs) and generative AI systems, including both text-based and multimodal models. Strong programming skills in Python, including proficiency with data science libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and/or PyTorch. Familiarity with MLOps principles and tools for automating and streamlining the ML lifecycle. Experience working with agentic AI. Capable of building Retrieval-Augmented Generation (RAG) pipelines leveraging vector stores like Pinecone, Chroma, or FAISS. Strong programming skills in Python, with experience using leading AI/ML libraries such as Hugging Face Transformers and LangChain. Practical experience in working with vector databases and embedding methodologies for efficient information retrieval. Possess experience in developing and exposing API endpoints for accessing AI model capabilities using frameworks like FastAPI. Knowledgeable in prompt engineering techniques, including prompt chaining and performance evaluation strategies. Solid grasp of natural language processing (NLP) fundamentals and transformer-based model architectures. Experience in deploying machine learning models to cloud platforms (preferably AWS) and containerized environments using Docker or Kubernetes. Skilled in fine-tuning and assessing open-source models using methods such as LoRA, PEFT, and supervised training. Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Able to operate successfully in a lean, fast-paced organization, and to create a vision and organization that can scale quickly Senior Gen AI Engineer

About the Role You’ll join a small, fast team turning cutting-edge AI research into shippable products across text, vision, and multimodal domains. One sprint you’ll be distilling an LLM for WhatsApp chat-ops; the next you’ll be converting CAD drawings to BOM stories, or training a computer-vision model that flags onsite safety risks. You own the model life-cycle end-to-end: data prep ➞ fine-tune/distil ➞ evaluate ➞ deploy ➞ monitor. Key Responsibilities Model Engineering • Fine-tune and quantise open-weight LLMs (Llama 3, Mistral, Gemma) and SLMs for low-latency edge inference. • Train or adapt computer-vision models (YOLO, Segment Anything, SAM-DINO) to detect site hazards, drawings anomalies, or asset states. Multimodal Pipelines • Build retrieval-augmented-generation (RAG) stacks: loaders → vector DB (FAISS / OpenSearch) → ranking prompts. • Combine vision + language outputs into single “scene → story” responses for dashboards and WhatsApp bots. Serving & MLOps • Package models as Docker images, SageMaker endpoints, or ONNX edge bundles; expose FastAPI/GRPC handlers with auth, rate-limit, telemetry. • Automate CI/CD: GitHub Actions → Terraform → blue-green deploys. Evaluation & Guardrails • Design automatic eval harnesses (BLEU, BERTScore, CLIP similarity, toxicity & bias checks). • Monitor drift, hallucination, latency; implement rollback triggers. Enablement & Storytelling • Write prompt playbooks & model cards so other teams can reuse your work. • Run internal workshops: “From design drawing to narrative” / “LLM safety by example”. Required Skills & Experience 3+ yrs ML/NLP/CV in production; at least 1 yr hands-on with Generative AI . Strong Python (FastAPI, Pydantic, asyncio) and HuggingFace Transformers OR diffusers . Experience with minima­l-footprint models (LoRA, QLoRA, GGUF, INT-4) and vector search. Comfortable on AWS/GCP/Azure for GPU instances, serverless endpoints, IaC. Solid grasp of evaluation/guardrail frameworks (Helm, PromptLayer, Guardrails-AI, Triton metrics). Bonus Points Built a RAG or function-calling agent used by 500+ users. Prior CV pipeline (object-detection, segmentation) or speech-to-text real-time project. Live examples of creative prompt engineering or story-generation. Familiarity with LangChain, LlamaIndex, or BentoML. Why You’ll Love It Multidomain playground – text, vision, storytelling, decision-support. Tech freedom – pick the right model & stack; justify it; ship it. Remote-first – work anywhere ±4 hrs of IST; quarterly hack-weeks in Hyderabad. Top-quartile pay – base + milestone bonus + conference stipend. How to Apply Send a resume and link to GitHub / HF / Kaggle showcasing LLM or CV work. Include a 200-word note describing your favourite prompt or model tweak and the impact it had. Short-listed candidates complete a practical take-home (fine-tune tiny model, build RAG or vision demo, brief write-up) and a 45-min technical chat. We hire builders, not resume keywords. Show us you can ship AI that works in the real world—and explain it clearly—and you’re in.

Job description About The Role: As a Subject Matter Expert (SME)/Team Lead in Data Annotation, you will play a critical role in ensuring the highest quality of data labelling across various projects. Technical and Domain expert Mentor annotation teams Establish annotation guidelines Conduct quality audits Support client and internal teams with domain-specific insights. Tools Experience Expected: CVAT, Amazon SageMaker, BasicAI, LabelStudio, SuperAnnotate, Loft, Cogito, Roboflow, Slicer3D, Mindkosh, Kognic, Praat Annotation Expertise Areas: Image, Video: Bounding Box, Polygon, Semantic Segmentation, Keypoints 3D Point Cloud: LiDAR Annotation, 3D Cuboids, Semantic Segmentation Audio Annotation: Speech, Noise Labelling, Transcription Text Annotation: NER, Sentiment Analysis, Intent Detection, NLP tasks Exposure to LLMs and Generative AI data annotation tasks (prompt generation, evaluation) Key Responsibilities: Act as a Subject Matter Expert to guide annotation standards, processes, and best practices. Create, refine, and maintain detailed annotation guidelines and ensure adherence across teams. Conduct quality audits and reviews to maintain high annotation accuracy and consistency. Provide domain-specific training to Data Annotators and Team Leads. Collaborate closely with Project Managers, Data Scientists, and Engineering teams for dataset quality assurance. Resolve complex annotation issues and edge cases with data-centric solutions. Stay current with advancements in AI/ML and annotation technologies and apply innovative methods. Support pre-sales and client discussions as an annotation domain expert, when required. Key Performance Indicators (KPIs): Annotation quality and consistency across projects Successful training and upskilling of annotation teams Timely resolution of annotation queries and technical challenges Documentation of guidelines, standards Client satisfaction on annotation quality benchmarks Qualifications: Bachelor's or master's degree in a relevant field (Computer Science, AI/ML, Data Science, Linguistics, Engineering, etc.) 3–6 years of hands-on experience in data annotation, with exposure to multiple domains (vision, audio, text, 3D). Deep understanding of annotation processes, tool expertise, and quality standards. Prior experience in quality control, QA audits, or SME role in annotation projects. Strong communication skills to deliver training, documentation, and client presentations. Familiarity with AI/ML workflows, data preprocessing, and dataset management concepts is highly desirable. Work Location: In-person (Salem, Tamil Nadu) Languages : Tamil(oral communication must),English,Hindi(Good to have) Schedule: Day Shift Monday to Saturday Weekend availability required Supplemental Pay: Overtime pays Performance bonus Shift allowance Yearly bonus Contact :9489979523(HR) Job Type: Full-time Schedule: Day shift Experience: data annotation: 2 years (Preferred) Work Location: In person

Required Skills & Experience: • 12+ years of experience in AI/ML, data engineering, and cloud architecture. • Minimum of 10 end-to-end AI/ML project implementations from use case discovery through to productionization. • Proven expertise in: (Any One) • AI/ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch • GenAI/LLM platforms: OpenAI, Cohere, Mistral, LangChain, Hugging Face, vector DBs (Pinecone, FAISS, Chroma) • Cloud platforms: AWS, Azure, GCP – including AI/ML & GenAI native services • MLOps/LLMOps tools: MLflow, Kubeflow, SageMaker Pipelines, Vertex AI Pipelines • Strong experience with data security, governance, model risk management, and AI compliance frameworks • Ability to lead large cross-functional teams and engage both technical teams and senior stakeholders

Description At Amazon, we're working to be the most customer-centric company on Earth. To get there, we need talented, bright, and data-driven people. If you'd like to help us build the place to find and buy anything online, this is your chance to make history. Within Amazon’s Workplace Health & Safety team, ‘The Employee Safety Experience (ESE)’ team is seeking an analytical and detail-oriented candidate. This is an exciting opportunity to join a team in a huge growth area for Amazon. The vision of this team is to build an Amazon safety experience that is responsive to our employees needs and actionable by our leaders. One of the vertical of ESE is ‘The Business and Program Analysis’ team with focus on providing technical guidance and thought leadership on all ESE programs from ideation through execution. The ideal candidate will have a strong analytical mindset, attention to detail, and the ability to communicate complex information clearly and concisely. You should be comfortable working with data, have basic SQL skills, and be eager to learn and grow in a fast-paced environment. Key job responsibilities Key Responsibilities Include Provide analytics solutions to solve business problems Extract available data and apply basic transformations using spreadsheets, SQL, and other relevant tools Use descriptive analysis techniques to understand impact and identify drivers Generate findings that inform team decisions by providing visibility to business performance, highlighting anomalies, and revealing new opportunities Document your analytical approach, including metric definitions, applied logic, assumptions, and data sources Work with technology teams to contribute towards development/ improvement of portals, dashboards and online tools including logic validation. Share findings with your team through written and verbal communication channels Learn and apply analytical best practices to improve team and process efficiency Help train new peers and contribute to the development of your team Basic Qualifications Bachelor's degree in a quantitative field (e.g., Business, Economics, Statistics, Mathematics, Computer Science) or equivalent practical experience Proficiency in Microsoft Excel and SQL skills Experience with data analysis and creating visualizations Knowledge of AI/ML tools and platforms (e.g., Amazon SageMaker, TensorFlow, Python libraries for data analysis) Understanding of basic machine learning concepts and their business applications Strong problem-solving and analytical skills Excellent written and verbal communication skills Ability to work effectively in a team environment Preferred Qualifications 3+ years of working experience in a data analysis or business intelligence role Experience with business intelligence tools (e.g., Tableau, QuickSight) Exposure to generative AI tools and their applications in business analytics Strong attention to detail and ability to manage multiple priorities Demonstrated ability to learn quickly and adapt to new technologies and processes Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI - Karnataka Job ID: A3014529

Develop and deploy ML models using SageMaker. Automate data pipelines and training processes. Monitor and optimize model performance. Ensure model governance and reproducibility.

Develop and deploy ML models using SageMaker. Automate data pipelines and training processes. Monitor and optimize model performance. Ensure model governance and reproducibility.

Who we are? Typeface is on a mission to help everyone express their unique imagination. We believe technology is a creative partner that empowers any company to tell their unique stories faster and easier than ever before. Generative AI platforms represent a major breakthrough to create content at tremendous speed and scale. For enterprises to successfully leverage their potential, they need to include their unique voice and style and ensure responsible AI practices. We unite content velocity with brand personalization and safety, so that every company can achieve its creative potential. We are looking for passionate individuals who want to help build a fast-growing GenAI company from the ground up. Why join us? Bleeding edge technology: We explore uncharted territory at the intersection of art and science. We strive to revolutionize content, amplifying human creativity with cutting-edge AI in a safe and responsible way. Best-in-class product: We built the leading enterprise-grade generative AI solution, so any business, from startups to Fortune 500 companies, can 10x personalized content at scale. Typeface combines the best-in-class AI platforms across the board with our own brand-personalized AI model to hyper-personalize content at scale with a responsible AI approach. World-class team: Founded by the former CPO & CTO of Adobe, Abhay Parasnis, and a highly experienced team with a proven track record of building revolutionary, long-lasting AI, SaaS, and media technologists that are completely focused on customer impact. Top-tier Investors: Backed by top-tier venture capital firms: Lightspeed Venture Partners, Salesforce Ventures, GV (Google Ventures), Madrona, Menlo Ventures, and M12 (Microsoft’s Venture Fund). Check out our Series B announcement. Rapid customer traction: Overwhelming demand from Fortune 500 companies and popular digital-native brands from every industry. Awards & recognition: Honored to be a winner of 10+ industry awards for our unique approach to enterprise GenAI, including Fast Company’s “Top 5 Next Big Things in Tech” and Adweek’s AI Company of the Year. The Mission: As an Applied Scientist , you will be responsible for building machine learning models/systems and innovative web applications that deliver the power of Generative AI to our customers. You will work closely with Researchers, Designers, Product Managers and engineers driving the technical designs and implementations. Core Responsibilities: We are looking for a strong Applied Scientist across multiple levels to join our team and help us build innovative Generative AI solutions that deliver the power of Generative AI to our customers. You will be responsible for: Developing cutting-edge machine learning and Generative AI models for image, text, audio and video Defining the roadmap for generation of various content types including text, image, audio and video enabling us to generate brand-affinitized, hyper-personalized, and safe content. Owning the delivery of key business, product and technology initiatives Establishing and implementing processes for model training, fine-tuning, testing, and operating the Generative AI models at significant scale. Investigation, prototyping and delivering innovative solutions. Establishing a data-driven development culture by driving the definition, tracking, and operationalizing of feature, product, and company-level metrics. Minimum Qualifications: Ph.D. in Computer Science, a related field, or equivalent practical experience. Specialization in Computer Vision, Natural Language Processing, Generative AI, or Multimodal learning. Proficiency in Python or C/C++. Proven track record of contributions to the research community, demonstrated through publications in top venues such as CVPR, ICML, ICLR, NeurIPS, etc. Have a track record of coming up with new ideas or improving upon existing approaches in machine learning, demonstrated by accomplishments such as first author publications or projects Ability to create self-contained, reusable, and testable modules and passionate about prototyping Preferred Qualifications: Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms 2+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning models at scale Hands-on experience in deploying and tuning Generative AI models Experience working at a high-growth startup or tech company Benefits for Full-time Employees: Medical, dental, and vision insurance coverage for all employees Competitive salary and equity compensation Flexible PTO Parental Leave Hybrid schedule with company provided lunch when in office Opportunities for professional growth and development Work with a fast-growing startup and be a part of an exciting journey Equality Opportunity Statement Typeface is an equal opportunity employer and does not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Diversity & Inclusion Statement At Typeface, we embrace everyone and believe that diversity and inclusion are essential to our success. We are committed to creating a workplace that is welcoming and inclusive for all employees, regardless of their background or identity. We value diversity in all its forms and strive to cultivate a culture where all employees can bring their best selves to work.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of L ead Consultant - C loud Engineer! In this role, you will be responsible for designing, provisioning, and securing scalable cloud infrastructure to support AI/ML and Generative AI workloads. A key focus will be ensuring high availability, cost efficiency, and performance optimization of infrastructure through best practices in architecture and automation. Responsibilities Design and implement secure VPC architecture, subnets, NAT gateways, and route tables. Build and maintain IAC modules for repeatable infrastructure provisioning. Build CI/CD pipelines that support secure, auto-scalable AI deployments using GitHub Actions, AWS CodePipeline , and Lambda triggers. Monitor and tune infrastructure health using AWS CloudWatch, GuardDuty , and custom alerting. Track and optimize cloud spend using AWS Cost Explorer, Trusted Advisor, and usage dashboards. Deploy and manage cloud-native services including SageMaker, Lambda, ECR, API Gateway etc. Implement IAM policies, Secrets Manager, and KMS encryption for secure deployments. Enable logging and monitoring using CloudWatch and configure alerts and dashboards. Set up and manage CloudTrail, GuardDuty , and AWS Config for audit and security compliance. Assist with cost optimization strategies including usage analysis and budget alerting. Support multi-cloud or hybrid integration patterns (e.g., data exchange between AWS and Azure/GCP). Collaborate with MLOps and Data Science teams to translate ML/ GenAI requirements into production-grade, resilient AWS environments. Maintain multi-cloud compatibility as needed (e.g., data egress readiness, common abstraction layers). Be engaging in the design, development and maintenance of data pipelines for various AI use cases Required to actively contribution to key deliverables as part of an agile development team Be collaborating with others to source, analyse, test and deploy data processes. Qualifications we seek in you! Minimum Qualifications AWS infrastructure experience in production environments. Degree/qualification in Computer Science or a related field, or equivalent work experience Proficiency in Terraform, AWS CLI, and Python or Bash scripting. Strong knowledge of IAM, VPC, ECS/EKS, Lambda, and serverless computing. Experience supporting AI/ML or GenAI pipelines in AWS (especially for compute and networking). Hands on experience to multiple AI / ML /RAG/LLM workloads and model deployment infrastructure. Exposure to multi-cloud architecture basics (e.g., SSO, networking, blob exchange, shared VPC setups). AWS Certified DevOps Engineer or Solutions Architect - Associate/Professional. Experience in developing, testing, and deploying data pipelines using public cloud. Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills Experience deploying infrastructure in both AWS and another major cloud provider (Azure or GCP). Familiarity with multi-cloud tools (e.g., HashiCorp Vault, Kubernetes with cross-cloud clusters). Strong understanding of DevSecOps best practices and compliance requirements. Exposure to RAG/LLM workloads and model deployment infrastructure. Knowledge of governance and compliance policies, standards, and procedures Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

About AiSensy AiSensy is a WhatsApp based Marketing & Engagement platform helping businesses like Adani, Delhi Transport Corporation, Yakult, Godrej, Aditya Birla Hindalco., Wipro, Asian Paints, India Today Group Skullcandy, Vivo, Physicswallah, Cosco grow their revenues via WhatsApp. Enabling 100,000+ Businesses with WhatsApp Engagement & Marketing 400Crores + WhatsApp Messages done between Businesses and Users via AiSensy per year Working with top brands like Delhi Transport Corporation, Vivo, Physicswallah & more High Impact as Businesses drive 25-80% Revenues using AiSensy Platform Mission-Driven and Growth Stage Startup backed by Marsshot.vc, Bluelotus.vc & 50+ Angel Investors About the Role We are seeking a highly skilled and innovative AI/ML Engineer to join our dynamic team. In this role, you will design, develop, and deploy cutting-edge artificial intelligence (AI) solutions, leveraging advanced machine learning (ML) techniques and AI frameworks to address complex business challenges. You will work closely with cross-functional teams to build intelligent systems and drive innovation, with a focus on implementing and optimizing modern AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents. Key Responsibilities AI Model Development Design, develop, and optimize AI solutions, including LLMs , RAG architectures , and Graph-based RAG systems , tailored to specific business needs. Develop and fine-tune models for tasks such as Natural Language Processing (NLP) , Computer Vision , and Reinforcement Learning (RL) . Prompt Engineering and AI Agents Work with prompt optimization to enhance LLM-based responses for specific use cases. Develop autonomous AI agents capable of completing multi-step tasks with minimal human intervention. Data Processing and Management Collect, clean, preprocess, and organize datasets for effective AI and ML model training and evaluation. Leverage graph databases and vector stores for efficient data retrieval in AI-driven systems. Algorithm Selection and Optimization Choose and implement appropriate algorithms, considering constraints such as scalability, interpretability, and real-time deployment requirements. Conduct hyperparameter tuning and optimization experiments to maximize model efficiency and accuracy. Deployment and Integration Deploy AI/ML models in production-grade environments , ensuring scalability, reliability, and seamless integration with existing systems. Implement model monitoring pipelines to ensure performance consistency over time. Research and Development Stay abreast of the latest trends and advancements in AI and ML technologies, such as transformer architectures , diffusion models , and multi-modal AI . Experiment with emerging tools like LangChain , Hugging Face , and OpenAI APIs to innovate solutions. Collaboration and Knowledge Sharing Work closely with data scientists, software engineers, and product managers to define project requirements and deliver impactful AI solutions. Document workflows, processes, and findings to enable knowledge sharing and continuity across teams. Required Qualifications Education Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, Mathematics, or a related field. Experience Minimum 3+ years in AI/ML roles with a proven track record in building and deploying AI-driven solutions. Technical Proficiency Proficiency in Python and AI/ML frameworks like TensorFlow , PyTorch , scikit-learn , or Keras . Experience working with LLMs , transformers , and generative AI tools . Familiarity with cloud platforms such as AWS , Google Cloud , or Azure , including AI-focused services like SageMaker and Vertex AI. Knowledge of vector databases (e.g., Pinecone, Milvus, Weaviate) and graph databases for RAG systems. Analytical Expertise Strong understanding of advanced statistical methods , mathematical concepts , and probabilistic models . Ability to analyze and interpret data for actionable insights and model improvements. Soft Skills Exceptional problem-solving and critical-thinking abilities. Strong communication skills to effectively collaborate with cross-functional teams. Adaptability to a fast-paced, innovation-driven environment. Preferred Qualifications Hands-on experience with LangChain , Hugging Face Transformers , or OpenAI API integrations . Expertise in specialized AI domains like multi-modal learning, conversational AI , and prompt engineering . Contributions to open-source AI projects or publications in recognized AI/ML conferences or journals. Familiarity with deploying AI Agents in production systems.

Senior Gen AI Engineer Job Description Brightly Software is seeking an experienced candidate to join our Product team in the role of Gen AI engineer to drive best in class client-facing AI features by creating and delivering insights that advise client decisions tomorrow. As a Gen AI Engineer, you will play a critical role in building AI offerings for Brightly. You will partner with our various software Product teams to drive client facing insights to inform smarter decisions faster. This will include the following: Lead the evaluation and selection of foundation models and vector databases based on performance and business needs Design and implement applications powered by generative AI (e.g., LLMs, diffusion models), delivering contextual and actionable insights for clients. Establish best practices and documentation for prompt engineering, model fine-tuning, and evaluation to support cross-domain generative AI use cases. Build, test, and deploy generative AI applications using standard tools and frameworks for model inference, embeddings, vector stores, and orchestration pipelines. Key Responsibilities: Guide the design of multi-step RAG, agentic, or tool-augmented workflows Implement governance, safety layers, and responsible AI practices (e.g., guardrails, moderation, auditability) Mentor junior engineers and review GenAI design and implementation plans Drive experimentation, benchmarking, and continuous improvement of GenAI capabilities Collaborate with leadership to align GenAI initiatives with product and business strategy Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector stores like Pinecone, FAISS, or AWS Opensearch Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for model building. Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, natural language processing) with strong exerience in predictive and stastical modelling. Implement and deploy machine learning models into production using AWS services, with a strong focus on Amazon SageMaker (e.g., SageMaker Studio, training jobs, inference endpoints, SageMaker Pipelines). Understanding and development of state management workflows using Langraph. Develop GenAI applications using Hugging Face Transformers, LangChain, and Llama related frameworks Engineer and evaluate prompts, including prompt chaining and output quality assessment Apply NLP and transformer model expertise to solve language tasks Deploy GenAI models to cloud platforms (preferably AWS) using Docker and Kubernetes Monitor and optimize model and pipeline performance for scalability and efficiency Communicate techn

Gen AI Engineer Job Description Brightly Software is seeking a high performer to join our Product team in the role of Gen AI engineer to drive best in class client-facing AI features by creating and delivering insights that advise client decisions tomorrow. As a Gen AI Engineer, you will play a critical role in building AI offerings for Brightly. You will partner with our various software Product teams to drive client facing insights to inform smarter decisions faster. This will include the following: Design and implement applications powered by generative AI (e.g., LLMs, diffusion models), delivering contextual and actionable insights for clients. Establish best practices and documentation for prompt engineering, model fine-tuning, and evaluation to support cross-domain generative AI use cases. Build, test, and deploy generative AI applications using standard tools and frameworks for model inference, embeddings, vector stores, and orchestration pipelines. Key Responsibilities: Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector stores like Pinecone, FAISS, or AWS OpenSearch Develop GenAI applications using Hugging Face Transformers, LangChain, and Llama related frameworks Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for model building. Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, natural language processing) with strong exerience in predictive and stastical modelling. Implement and deploy machine learning models into production using AWS services, with a strong focus on Amazon SageMaker (e.g., SageMaker Studio, training jobs, inference endpoints, SageMaker Pipelines). Understanding and development of state management workflows using Langraph. Engineer and evaluate prompts, including prompt chaining and output quality assessment Apply NLP and transformer model expertise to solve language tasks Deploy GenAI models to cloud platforms (preferably AWS) using Docker and Kubernetes Monitor and optimize model and pipeline performance for scalability and efficiency Communicate technical concepts clearly to cross-functional and non-technical stakeholders Thrive in a fast-paced, lean environment and contribute to scalable GenAI system design Qualifications Bachelor’s degree is required 2-4 years of experience of total experience with a strong focus on AI and ML and 1+ years in core GenAI Engineering Demonstrated expertise in working with large language models (LLMs) and generative AI systems, including both text-based and multimodal models. Strong programming skills in Python, including proficiency with data science libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and/or PyTorch. Familiarity with MLOps principles and tools for automating and streamlining the ML lifecycle. Experience working with agentic AI. Capable of building Retrieval-Augmented Generation (RAG) pipelines leveraging vector stores like Pinecone, Chroma, or FAISS. Strong programming skills in Python, with experience using leading AI/ML libraries such as Hugging Face Transformers and LangChain. Practical experience in working with vector databases and embedding methodologies for efficient information retrieval. Possess experience in developing and exposing API endpoints for accessing AI model capabilities using frameworks like FastAPI. Knowledgeable in prompt engineering techniques, including prompt chaining and performance evaluation strategies. Solid grasp of natural language processing (NLP) fundamentals and transformer-based model architectures. Experience in deploying machine learning models to cloud platforms (preferably AWS) and containerized environments using Docker or Kubernetes. Skilled in fine-tuning and assessing open-source models using methods such as LoRA, PEFT, and supervised training. Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Able to operate successfully in a lean, fast-paced organization, and to create a vision and organization that can scale quickly Senior Gen AI Engineer

Ready to shape the future of work? At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory , our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI , our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn , X , YouTube , and Facebook . Inviting applications for the role of L ead Consultant - C loud Engineer! In this role, you will be responsible for designing, provisioning, and securing scalable cloud infrastructure to support AI/ML and Generative AI workloads. A key focus will be ensuring high availability, cost efficiency, and performance optimization of infrastructure through best practices in architecture and automation. Responsibilities Design and implement secure VPC architecture, subnets, NAT gateways, and route tables. Build and maintain IAC modules for repeatable infrastructure provisioning. Build CI/CD pipelines that support secure, auto-scalable AI deployments using GitHub Actions, AWS CodePipeline , and Lambda triggers. Monitor and tune infrastructure health using AWS CloudWatch, GuardDuty , and custom alerting. Track and optimize cloud spend using AWS Cost Explorer, Trusted Advisor, and usage dashboards. Deploy and manage cloud-native services including SageMaker, Lambda, ECR, API Gateway etc. Implement IAM policies, Secrets Manager, and KMS encryption for secure deployments. Enable logging and monitoring using CloudWatch and configure alerts and dashboards. Set up and manage CloudTrail, GuardDuty , and AWS Config for audit and security compliance. Assist with cost optimization strategies including usage analysis and budget alerting. Support multi-cloud or hybrid integration patterns (e.g., data exchange between AWS and Azure/GCP). Collaborate with MLOps and Data Science teams to translate ML/ GenAI requirements into production-grade, resilient AWS environments. Maintain multi-cloud compatibility as needed (e.g., data egress readiness, common abstraction layers). Be engaging in the design, development and maintenance of data pipelines for various AI use cases Required to actively contribution to key deliverables as part of an agile development team Be collaborating with others to source, analyse, test and deploy data processes. Qualifications we seek in you! Minimum Qualifications AWS infrastructure experience in production environments. Degree/qualification in Computer Science or a related field, or equivalent work experience Proficiency in Terraform, AWS CLI, and Python or Bash scripting. Strong knowledge of IAM, VPC, ECS/EKS, Lambda, and serverless computing. Experience supporting AI/ML or GenAI pipelines in AWS (especially for compute and networking). Hands on experience to multiple AI / ML /RAG/LLM workloads and model deployment infrastructure. Exposure to multi-cloud architecture basics (e.g., SSO, networking, blob exchange, shared VPC setups). AWS Certified DevOps Engineer or Solutions Architect – Associate/Professional. Experience in developing, testing, and deploying data pipelines using public cloud. Clear and effective communication skills to interact with team members, stakeholders and end users Preferred Qualifications/ Skills Experience deploying infrastructure in both AWS and another major cloud provider (Azure or GCP). Familiarity with multi-cloud tools (e.g., HashiCorp Vault, Kubernetes with cross-cloud clusters). Strong understanding of DevSecOps best practices and compliance requirements. Exposure to RAG/LLM workloads and model deployment infrastructure. Knowledge of governance and compliance policies, standards, and procedures Why join Genpact? Be a transformation leader – Work at the cutting edge of AI, automation, and digital innovation Make an impact – Drive change for global enterprises and solve business challenges that matter Accelerate your career – Get hands-on experience, mentorship, and continuous learning opportunities Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training. Job Lead Consultant Primary Location India-Hyderabad Schedule Full-time Education Level Bachelor's / Graduation / Equivalent Job Posting Jun 19, 2025, 11:01:58 PM Unposting Date Ongoing Master Skills List Digital Job Category Full Time

- 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language Have you ever been shown an irrelevant ad? How about and an embarrassing one with a child or parent watching? Here, you can help us be part of Amazon's solution to ensuring you and millions of customer like you never face this. Here, you can help us make a world wide impact on the Amazon Advertising experience. Amazon is investing in building a world class advertising business and our team is responsible for ensuring that the ads served to customers meet the same high quality bar that you've come to love and trust. We're looking for an outstanding candidate to join us as a full-time Software Development Engineer. You will work as part of an agile team to help drive automation of ad moderation, quality, and content checks world wide. As an engineer, you will be involved in the full software development lifecycle from idea generation to delivery and operation. Successful candidates are not just great coders, they are engineers who can delight customers through innovation, have excellent communication and collaboration skills and are motivated to build lasting full stack technologies using the latest systems like AWS Lambda, DynamoDB, and AWS Sagemaker. Bring all that you already know and come ready and eager to learn and innovate together. Key job responsibilities • Research, design and code, troubleshoot and support. What you create is also what you own. Own systems end-to-end including requirements clarification, design, implementation and roll-out to customers. • Improve the team's development processes and thereby increase developer productivity. • Coach junior members of the team, and actively participate in code and design reviews. • Contribute to evolving the technical direction of Ad Trust and play a critical role their design and development A day in the life As a Software Development Engineer in the Ad Trust engineering team • You will build engineering systems and features to support human ad moderation. • You will also build scalable tools and infrastructure that will be used to measure moderation quality. • You will be challenged to work on optimisation problem for moderation task routing algorithm. • You will get to use latest distributed systems and big data technologies such as AWS Lambda, ECS, Elastic Search, DDB, SQS, SNS, Apache Spark, and EMR. About the team The Advertising Trust (AT) organization is at the center of Amazon Ads, one of Amazon’s fastest growing businesses. Every ad that flows through our Amazon systems, or is presented on one of our owned and operated sites, needs to adhere to the policies that AT creates. we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Bachelor's degree in computer science or equivalent Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Gurgaon 4 3+ Years Full Time We are looking for a technically adept and instructionally strong AI Developer with core expertise in Python, Large Language Models (LLMs), prompt engineering, and vector search frameworks such as FAISS, LlamaIndex, or RAG-based architectures. The ideal candidate combines solid foundations in data science, statistics, and machine learning development with a hands-on understanding of ML DevOps, model selection, and deployment pipelines. 3–4 years of experience in applied machine learning or AI development, including at least 1–2 years working with LLMs, prompt engineering, or vector search systems. Core Skills Required: Python: Advanced-level expertise in scripting, data manipulation, and model development LLMs (Large Language Models): Practical experience with GPT, LLaMA, Mistral, or open- source transformer models Prompt Engineering: Ability to design, optimize, and instruct on prompt patterns for various use cases Vector Search & RAG: Understanding of feature vectors, nearest neighbor search, and retrieval-augmented generation (RAG) using tools like FAISS, Pinecone, Chroma, or Weaviate LlamaIndex: Experience building AI applications using LlamaIndex, including indexing documents and building query pipelines Rack Knowledge: Familiarity with RACK architecture, model placement, and scaling on distributed hardware ML / ML DevOps: Knowledge of full ML lifecycle including feature engineering, model selection, training, and deployment Data Science & Statistics: Solid grounding in statistical modeling, hypothesis testing, probability, and computing concepts Responsibilities: Design and develop AI pipelines using LLMs and traditional ML models Build, fine-tune, and evaluate large language models for various NLP tasks Design prompts and RAG-based systems to optimize output relevance and factual grounding Implement and deploy vector search systems integrated with document knowledge bases Select appropriate models based on data and business requirements Perform data wrangling, feature extraction, and model training Develop training material, internal documentation, and course content (especially around Python and AI development using LlamaIndex) Work with DevOps to deploy AI solutions efficiently using containers, CI/CD, and cloud infrastructure Collaborate with data scientists and stakeholders to build scalable, interpretable solutions Maintain awareness of emerging tools and practices in AI and ML ecosystems Preferred Tools & Stack: Languages: Python, SQL ML Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers Vector DBs: FAISS, Pinecone, Chroma, Weaviate RAG Tools: LlamaIndex, LangChain ML Ops: MLflow, DVC, Docker, Kubernetes, GitHub Actions Data Tools: Pandas, NumPy, Jupyter Visualization: Matplotlib, Seaborn, Streamlit Cloud: AWS/GCP/Azure (S3, Lambda, Vertex AI, SageMaker) Ideal Candidate: Background in Data Science, Statistics, or Computing Passionate about emerging AI tech, LLMs, and real-world applications Demonstrates both hands-on coding skills and teaching/instructional abilities Capable of building reusable, explainable AI solutions Location gurgaon sector 49

We are looking for a hands-on AI Engineer / Data Scientist with deep expertise in Natural Language Processing (NLP) and Large Language Models (LLMs) . The ideal candidate will have experience building custom AI models from the ground up, optimizing for performance, and integrating them into real-world systems and applications. Key Responsibilities: Design, build, and deploy NLP and LLM-based models tailored to domain-specific needs (e.g., chatbots, summarization, classification). Fine-tune and adapt foundation models (e.g., GPT, LLaMA, Mistral) for business use cases. Build custom pipelines for text processing, entity recognition, language understanding, and speech-to-text integrations. Work closely with engineering teams to integrate AI models into production systems (APIs, microservices, and edge deployments). Conduct experimentation, model evaluations , and performance tuning for latency, accuracy, and scalability. Collaborate cross-functionally with product, infra, and DevOps teams to ensure smooth deployment and monitoring of model Required Skills & Experience: 3-6 Years of relevant Experience Strong experience with Python , PyTorch , or TensorFlow . Proven track record in training, fine-tuning , and deploying LLMs or transformer-based models (BERT, GPT, T5, etc.). Solid understanding of NLP fundamentals – tokenization, embeddings, attention, text classification, sequence labeling, etc. Experience with model deployment tools : FastAPI, Flask, Docker, REST APIs. Exposure to data pipelines and MLOps tools (MLflow, Weights & Biases, SageMaker, etc.). Knowledge of speech-based interfaces or integration with telephony/speech systems is a strong plus. Ability to translate business problems into AI solutions. Experience with RAG (Retrieval Augmented Generation) pipelines. Familiarity with LangChain, LlamaIndex , or similar agentic/LLM orchestration tools. Understanding of model security, prompt injection risks , and observability . Pls share below details with updated CV to shruti.solasi@movius.ai if the JD suits your profile: EXP CTC ECTC Location Notice Regards, Shruti

Description Have you ever been shown an irrelevant ad? How about and an embarrassing one with a child or parent watching? Here, you can help us be part of Amazon's solution to ensuring you and millions of customer like you never face this. Here, you can help us make a world wide impact on the Amazon Advertising experience. Amazon is investing in building a world class advertising business and our team is responsible for ensuring that the ads served to customers meet the same high quality bar that you've come to love and trust. We're looking for an outstanding candidate to join us as a full-time Software Development Engineer. You will work as part of an agile team to help drive automation of ad moderation, quality, and content checks world wide. As an engineer, you will be involved in the full software development lifecycle from idea generation to delivery and operation. Successful candidates are not just great coders, they are engineers who can delight customers through innovation, have excellent communication and collaboration skills and are motivated to build lasting full stack technologies using the latest systems like AWS Lambda, DynamoDB, and AWS Sagemaker. Bring all that you already know and come ready and eager to learn and innovate together. Key job responsibilities Research, design and code, troubleshoot and support. What you create is also what you own. Own systems end-to-end including requirements clarification, design, implementation and roll-out to customers. Improve the team's development processes and thereby increase developer productivity. Coach junior members of the team, and actively participate in code and design reviews. Contribute to evolving the technical direction of Ad Trust and play a critical role their design and development A day in the life As a Software Development Engineer in the Ad Trust engineering team You will build engineering systems and features to support human ad moderation. You will also build scalable tools and infrastructure that will be used to measure moderation quality. You will be challenged to work on optimisation problem for moderation task routing algorithm. You will get to use latest distributed systems and big data technologies such as AWS Lambda, ECS, Elastic Search, DDB, SQS, SNS, Apache Spark, and EMR. About The Team The Advertising Trust (AT) organization is at the center of Amazon Ads, one of Amazon’s fastest growing businesses. Every ad that flows through our Amazon systems, or is presented on one of our owned and operated sites, needs to adhere to the policies that AT creates. we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Basic Qualifications 3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience Experience programming with at least one software programming language Preferred Qualifications 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Bachelor's degree in computer science or equivalent Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI - Haryana Job ID: A3013926