1575 Sagemaker Jobs - Page 35

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

About the Role We’re seeking a mid-level AI/ML engineer who has 3–4 years of end-to-end model-development experience and is fluent with AWS services . You’ll join a fast-growing team that ships production-grade ML and GenAI features for global clients. Guide your team. What You’ll Do Data & Features: ingest, clean, and engineer structured/unstructured data from S3, RDS, Redshift, DynamoDB, Kinesis, etc. Modeling: build, train, and evaluate classical ML, deep-learning, and GenAI models with Amazon SageMaker, Bedrock, and related SDKs. MLOps: Use standard CI/CD and infrastructure-as-code practices to move models smoothly from development to production. Monitoring & Iteration: track drift/accuracy, run A/B tests, retrain, and tune for cost/performance. Collaboration: translate business problems into ML solutions alongside data engineers, front-end devs, and product managers. Must-have qualifications 3–4 years building and deploying AI/ML solutions in production. Hands-on expertise with the AWS AI/ML stack (SageMaker, Bedrock, Comprehend, Rekognition, Glue, Athena…). Strong Python plus ML libraries (scikit-learn, PyTorch or TensorFlow, Hugging Face). Solid grasp of data-engineering concepts (ETL pipelines, data lakes/warehouses). Ability to explain trade-offs to both technical and non-technical stakeholders. How to apply Email careers@jitglobalinfosystems.com with subject “AI/ML Engineer – ” and include Your résumé or LinkedIn profile.

We are seeking a passionate AI/ML Engineer to join our team in building the core AI-driven functionality an intelligent visual data encryption system. The role involves designing, training, and deploying AI models (e.g., CLIP, DCGANs, Decision Trees), integrating them into a secure backend, and operationalizing the solution via AWS cloud services and Python-based APIs. Key Responsibilities: AI/ML Development Design and train deep learning models for image classification and sensitivity tagging using CLIP, DCGANs, and Decision Trees. Build synthetic datasets using DCGANs for balancing. Fine-tune pre-trained models for customized encryption logic. Implement explainable classification logic for model outputs. Validate model performance using custom metrics and datasets. API Development Design and develop Python RESTful APIs using FastAPI or Flask for: Image upload and classification Model inference endpoints Encryption trigger calls Integrate APIs with AWS Lambda and Amazon API Gateway. AWS Integration Deploy and manage AI models on Amazon SageMaker for training and real-time inference. Use AWS Lambda for serverless backend compute. Store encrypted image data on Amazon S3 and metadata on Amazon RDS (PostgreSQL). Use AWS Cognito for secure user authentication and KMS for key management. Monitor job status via CloudWatch and enable secure, scalable API access. Required Skills & Experience: Must-Have 3–5 years of experience in AI/ML (especially vision-based systems). Strong experience with PyTorch or TensorFlow for model development. Proficient in Python with experience building RESTful APIs. Hands-on experience with Amazon SageMaker, Lambda, API Gateway, and S3. Knowledge of OpenSSL/PyCryptodome or basic cryptographic concepts. Understanding of model deployment, serialization, and performance tuning. Nice-to-Have Experience with CLIP model fine-tuning. Familiarity with Docker, GitHub Actions, or CI/CD pipelines. Experience in data classification under compliance regimes (e.g., GDPR, HIPAA). Familiarity with multi-tenant SaaS design patterns. Tools & Technologies: Python, PyTorch, TensorFlow FastAPI, Flask AWS: SageMaker, Lambda, S3, RDS, Cognito, API Gateway, KMS Git, Docker, Postgres, OpenCV, OpenSSL

Data Operations Engineer What You’ll Do Operations Support ● Monitor and triage production data pipelines, ingestion jobs, and transformation workflows (e.g. dbt, Fivetran, Snowflake tasks) ● Manage and resolve data incidents and operational issues, working cross-functionally with platform, data, and analytics teams ● Develop and maintain internal tools/scripts for observability, diagnostics, and automation of data workflows ● Participate in on-call rotations to support platform uptime and SLAs Data Platform Engineering Support ● Help manage infrastructure-as-code configurations (e.g., Terraform for Snowflake, AWS, Airflow) ● Support user onboarding, RBAC permissioning, and account provisioning across data platforms ● Assist with schema and pipeline changes, versioning, and documentation ● Assist with setting up monitoring on new pipelines in metaplane Data & Analytics Engineering Support ● Diagnosing model failures and upstream data issues ● Collaborate with analytics teams to validate data freshness, quality, and lineage ● Coordinate and perform backfills, schema adjustments, and reprocessing when needed ● Manage operational aspects of source ingestion (e.g., REST APIs, batch jobs, database replication, kafka) (confirm the writeup with Jason Prentice) ML-Ops & Data Science Infrastructure ● Collaborate with the data science team to operationalize and support ML pipelines, removing the burden of infrastructure ownership from the team ● Monitor ML batch and streaming jobs (e.g., model scoring, feature engineering, data preprocessing) ● Maintain and improve scheduling, resource management, and observability for ML workflows (e.g., using Airflow, SageMaker, or Kubernetes-based tools) ● Help manage model artifacts, metadata, and deployment environments to ensure reproducibility and traceability ● Support the transition of ad hoc or experimental pipelines into production-grade services What We’re Looking For Required Qualifications ● At least 2–4 years of experience in data engineering, DevOps, or data operations roles ● Solid understanding of modern data stack components (Snowflake, dbt, Airflow, Fivetran, cloud storage) ● Proficiency with SQL and comfort debugging data transformations or analytic queries ● Basic scripting/programming skills (e.g., Python, Bash) for automation and tooling ● Familiarity with version control (Git) and CI/CD pipelines for data projects ● Strong troubleshooting and communication skills — you enjoy helping others and resolving issues ● Experience with infrastructure-as-code (Terraform, CloudFormation) ● Familiarity with observability tools such as datadog ● Exposure to data governance tools and concepts (e.g., data catalogs, lineage, access control) ● Understanding of ELT best practices and schema evolution in distributed data systems

Data Scientist Hyderabad, 3 days WFO Highly skilled data scientist who will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. 4 to 7 years (II) of proven experience as a Data Scientist or in a similar role. Collaborate with AI/ML engineers, and architects to research, design, develop, and evaluate cutting-edge AI & generative AI models Build Train & Deploy AI Models to address real-world challenges Expertise working on AI platforms such as Dataiku, AWS Sagemaker, Bedrock, Snowflake Cortex AI etc. Interact with customers directly to understand the business problem, help and aid them in implementation of AI & generative AI solutions, deliver briefing and deep dive sessions to customers and guide customers on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholders Provide customer and market feedback to Product and Engineering teams to help define product direction Strong communication and client-facing skills, with the ability to translate technical concepts into business terms.

At AryaXAI , we’re building the future of explainable, scalable, and aligned AI —designed specifically for high-stakes environments where trust, transparency, and performance are non-negotiable. From financial services to energy and other regulated industries, our platform powers intelligent decision-making through safe and robust AI systems. We’re looking for a Data Scientist with a deep understanding of both classical and deep learning techniques, experience building enterprise-scale ML pipelines, and the ambition to tackle real-world, high-impact problems. You will work at the intersection of modeling, infrastructure, and regulatory alignment—fine-tuning models that must be auditable, performant, and production-ready. Responsibilities: Modeling & AI Development Design, build, and fine-tune machine learning models (both classical and deep learning) for complex mission-critical use cases in domains like banking, finance, energy, etc. Work on supervised, unsupervised, and semi-supervised learning problems using structured, unstructured, and time-series data. Fine-tune foundation models for specialized use cases requiring high interpretability and performance. Platform Integration Develop and deploy models on AryaXAI’s platform to serve real-time or batch inference needs. Leverage explainability tools (e.g., DLBacktrace, SHAP, LIME, or AryaXAI’s native xai_evals stack) to ensure transparency and regulatory compliance. Design pipelines for data ingestion, transformation, model training, evaluation, and deployment using MLOps best practices. Enterprise AI Architecture Collaborate with product and engineering teams to implement scalable and compliant ML pipelines across cloud and hybrid environments. Contribute to designing secure, modular AI workflows that meet enterprise needs—latency, throughput, auditability, and policy constraints. Ensure models meet strict regulatory and ethical requirements (e.g., bias mitigation, traceability, explainability). Requirements : 3+ years of experience building ML systems in production, ideally in regulated or enterprise environments. Strong proficiency in Python , with experience in libraries like scikit-learn, XGBoost, PyTorch, TensorFlow , or similar. Experience with end-to-end model lifecycle : from data preprocessing and feature engineering to deployment and monitoring. Deep understanding of enterprise ML architecture —model versioning, reproducibility, CI/CD for ML, and governance. Experience working with regulatory, audit, or safety constraints in data science or ML systems. Familiarity with ML Ops tools (MLflow, SageMaker, Vertex AI, etc.) and cloud platforms (AWS, Azure, GCP). Strong communication skills and an ability to translate technical outcomes into business impact. Bonus Points For Prior experience in regulated industries : banking, insurance, energy, or critical infrastructure. Experience with time-series modeling , anomaly detection, underwriting, fraud detection or risk scoring systems. Knowledge of RAG architectures , generative AI , or foundation model fine-tuning . Exposure to privacy-preserving ML , model monitoring , and bias mitigation frameworks. What You’ll Get Competitive compensation with performance-based upside Comprehensive health coverage for you and your family Opportunity to work on mission-critical AI systems where your models drive real-world decisions Ownership of core components in a platform used by top-tier enterprises Career growth in a fast-paced, high-impact startup environment Remote-first, collaborative, and high-performance team culture If you’re excited to build data science solutions that truly matter , especially in the most demanding industries, we want to hear from you.

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position A healthier future. That’s what drives us. We are looking for a highly skilled Artificial Intelligence (AI) / Machine Learning (ML) Engineer with expertise in building AI-powered applications. We will be building AI & GenAI solutions end-to-end: from concept, through prototyping, production, to operations. The Opportunity: Generative AI Application Development: Collaborate with developers and stakeholders in Agile teams to integrate LLMs and classical AI techniques into end-user applications, focusing on user experience, and real-time performance Algorithm Development: Design, develop, customize, optimize, and fine-tune LLM-based and other AI-infused algorithms tailored to specific use cases such as text generation, summarization, information extraction, chatbots, AI agents, code generation, document analysis, sentiment analysis, data analysis, etc LLM Fine-Tuning and Customization: Fine-tune pre-trained LLMs to specific business needs, leveraging prompt engineering, transfer learning, and few-shot techniques to enhance model performance in real-world scenarios End-to-End Pipeline Development: Build and maintain production-ready end-to-end ML pipelines, including data ingestion, preprocessing, training, evaluation, deployment, and monitoring; automate workflows using MLOps best practices to ensure scalability and efficiency Performance Optimization: Optimize model inference speed, reduce latency, and manage resource usage across cloud services and GPU/TPU architectures Scalable Model Deployment: Collaborate with other developers to deploy models at scale, using cloud-based infrastructure (AWS, Azure) and ensuring high availability and fault tolerance Monitoring and Maintenance: Implement continuous monitoring and refining strategies for deployed models, using feedback loops and e.g. incremental fine-tuning to ensure ongoing accuracy and reliability; address drifts and biases as they arise Software Development: Apply software development best practices, including writing unit tests, configuring CI/CD pipelines, containerizing applications, prompt engineering and setting up APIs; ensure robust logging, experiment tracking, and model monitoring Who are: Minimum overall 5-7 years of experience and hold B.Sc., B.Eng., M.Sc., M.Eng., Ph.D. or D.Eng. in Computer Science or equivalent degree Experience: 3+ years of experience in AI/ML engineering, with exposure to both classical machine learning methods and language model-based applications Technical Skills: Advanced proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; expertise with Transformer architectures; hands-on experience with LangChain or similar LLM frameworks; experience with designing end-to-end RAG systems using state of the art orchestration frameworks (hands on experience with fine-tuning LLMs for specific tasks and use cases considered as an additional advantage) MLOps Knowledge: Strong understanding of MLOps tools and practices, including version control, CI/CD pipelines, containerization, orchestration, Infrastructure as Code, automated deployment Deployment: Experience in deploying LLM and other AI models with cloud platforms (AWS, Azure) and machine learning workbenches for robust and scalable productizations Practical overview and experience with AWS services to design cloud solutions, familiarity with Azure is a plus; experience with working with GenAI specific services like Azure OpenAI, Amazon Bedrock, Amazon SageMaker JumpStart, etc. Data Engineering: Expertise in working with structured and unstructured data, including data cleaning, feature engineering with data stores like vector, relational, NoSQL databases and data lakes through APIs Model Evaluation and Metrics: Proficiency in evaluating both classical ML models and LLMs using relevant metrics Relocation benefits are not available for this posting. Who we are A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact. Let’s build a healthier future, together. Roche is an Equal Opportunity Employer.

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. Role As a Gen AI Engineer , you will play a critical role in building AI offerings for Brightly. Y ou 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. Role As a Gen AI Engineer , you will play a critical role in building AI offering s for Brightly. Y ou 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 D evelop 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 ex erience 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 Engineer ing Demonstrated expertise in working with large language models (LLMs) and generative AI systems, including both text-based and multimodal models. S trong 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. St rong 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. P ossess 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