2024 Inference Jobs - Page 4

100% ONSITE - 5 Days office - Sat & Sun Off Position: AI Developer Experience: 6 to 8 Years Location: Hyderabad (Mandatory) Work Mode: 5 Days Work from Office Key Responsibilities: Design, develop, and deploy AI-powered agents and intelligent automation solutions. Work extensively with LLMs, NLP, and ML/DL frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers). Integrate AI solutions into enterprise systems and business processes using APIs and RPA tools like UiPath or Automation Anywhere. Fine-tune and optimize pre-trained AI models focusing on scalability, accuracy, and performance. Collaborate with cross-functional teams – Product, Data Engineering, DevOps, and Business Stakeholders. Stay updated with the latest AI advancements and apply them to business solutions. Maintain proper documentation and testing protocols for AI solutions. Required Skills & Qualifications: 6–8 years of hands-on experience in AI development. Expertise in: LLMs (GPT, BERT, LLaMA, etc.) ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) NLP techniques (classification, NER, summarization) RPA tools and AI integration Proficient in Python (must), and optionally Java/C++. Strong knowledge of fine-tuning, prompt engineering, and inference optimization. Excellent problem-solving and cross-functional communication skills. DFusY9IqqR

We are seeking a highly skilled AI Engineer with a strong foundation in machine learning, deep learning, cloud platforms , and computer vision to join our innovative tech team. You’ll design and implement scalable AI/ML pipelines, automate workflows, train and optimize models, and deploy solutions on cloud infrastructure. This is an opportunity to shape the future of intelligent systems across industries. Key Responsibilities: Design, develop, and deploy ML/DL models for various applications, including computer vision and predictive analytics. Build data pipelines and model training workflows on cloud platforms such as AWS, Azure, or GCP. Automate model retraining, evaluation, and deployment processes using MLOps best practices. Collaborate with cross-functional teams (data engineers, product managers, developers) to define project requirements and deliver AI-powered features. Develop and fine-tune custom algorithms tailored to specific domain problems. Integrate AI solutions into existing systems using APIs, containers, and cloud-native tools. Conduct data preprocessing, exploratory data analysis, and feature engineering. Research and evaluate the latest AI trends, tools, and frameworks to recommend enhancements. Write clear, maintainable, and efficient code with documentation for reproducibility and scaling. Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related fields. 3+ years of hands-on experience in building and deploying machine learning/deep learning models. Strong programming skills in Python and frameworks like TensorFlow, PyTorch, OpenCV, Scikit-learn. Experience with computer vision libraries (OpenCV, YOLO, Detectron2, etc.). Proficiency in cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML Studio). Experience with Docker, Kubernetes, or other orchestration tools. Familiarity with MLOps tools like MLflow, DVC, Kubeflow, or Airflow. Solid understanding of algorithms, data structures, and model optimization techniques. Exposure to RESTful APIs and real-time inference systems. Strong analytical, problem-solving, and communication skills. Nice to Have: Experience with NLP models and transformers (e.g., Hugging Face). Experience deploying models at scale in production environments. Knowledge of CI/CD pipelines for AI applications. Publications or contributions to open-source AI projects. Why Join Us? Job Type: Permanent Pay: ₹20,000.00 - ₹50,000.00 per month Work Location: In person

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Head of AI Enablement to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you. Responsibilities: Identify all engineering processes suitable for AI automation (requirements, design, coding, testing, deployment) Deploy OpenAI Codex, ChatGPT Enterprise, Claude, OpenRouter, and RAG-based toolchains into daily dev workflows Collaborate with DevOps and Head of SaaS to automate onboarding, support, and configuration steps Partner with Internal Auditor to measure performance uplift and automation ROI Build AI-first internal apps: prompt libraries, RAG knowledge bots, test generators, doc writers Provide technical leadership on AI/LLM integration: APIs, inference cost, prompt engineering Educate engineering leaders on AI-first delivery models and productivity playbooks 5+ years in AI/ML engineering or Dev Tooling (AI-focused) Experience deploying AI/LLM agents into real-world product/dev orgs Strong understanding of LangChain, OpenRouter, RAG pipelines, OpenWebUI Experience from AI-native companies like Replit, Notion, OpenAI, HuggingFace, Retool Capable of owning AI adoption strategy and executing hands-on

Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission. As Microsoft's cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the SW/FW Centre of Excellence team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for seasoned engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure. We are looking for a highly motivated Senior Software Engineer with a track record in Cloud Service development to come help us develop and light up innovative AI-based solutions to improve engineering efficiency across development, validation and monitoring. To be successful in this role, you must have a great track record of delivering quality results to customers, an engineering mindset, an innate aptitude for agility, and technical excellence in software engineering. #SCHIE Responsibilities Design and implement AI agents using modern agent development frameworks (e.g., Semantic Kernel, AutoGen, AI Foundry). Build scalable, production-grade AI services that integrate with enterprise systems and workflows. Collaborate with cross-functional teams to define agent capabilities, communication protocols, and compliance requirements. Optimize agent performance for real-time inference and continuous learning. Qualifications Required Qualifications Bachelor’s degree in Computer Science, Computer Engineering, or a related field. 6+ years of industry experience in AI/ML engineering using platforms and languages/frameworks such as Python, Semantic Kernel, AutoGen, Azure AI Foundry, Mem0, Azure AI Search. Proven experience in designing, building, and deploying AI agents across the autonomy spectrum—from retrieval-based to task-oriented and autonomous agents. Strong background in developing web applications and services that integrate AI/ML models for business insights and automation. Preferred Qualifications Hands-on experience with large language models (LLMs), including training, fine-tuning, and inference optimization for multi-billion parameter models. Familiarity with the full ML lifecycle: data engineering, model training, evaluation, deployment, and monitoring. Understanding of embedded systems, firmware development, OS concepts is a strong plus. Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter. Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Education Preference- Only B.tech CS/IT Graduate from the batch of 2026/2025/2024 Job Description- Key Responsibilities: Collect and curate large-scale botanical image datasets, including scraping from online sources and organizing local image repositories with proper structure and naming conventions. Manually annotate plant images with precision (leaf, flower, fruit, stem, etc.) using tools like CVAT, LabelImg, or Labelme, while ensuring consistency and reviewing for quality. Assist in the pre-processing of image data (e.g., resizing, filtering, normalization, and augmentation) and monitor automated pipelines for correctness and completeness. Help validate annotations and perform sanity checks through basic machine learning inference (e.g., verifying predictions from classification or segmentation models). Collaborate closely with ML teams to flag edge cases, improve annotation guidelines, and maintain high data hygiene throughout the pipeline. Requirements: Prior experience handling large-scale image datasets (ideally in the terabyte range) and a strong understanding of digital image formats and metadata handling. Knowledge of plant/botanical structures and ability to visually distinguish between different parts (e.g., leaf vs. flower), preferably with academic or project exposure. Proficiency in basic Python scripting — familiarity with os, pandas, opencv, Pillow and ability to automate repetitive data handling tasks. Understanding of image annotation workflows and tools (CVAT, LabelImg, Labelme), plus familiarity with pre-processing and augmentation techniques commonly used in computer vision. Basic exposure to machine learning concepts such as image classification, segmentation, and inference, along with the discipline to carry out repetitive annotation tasks with high accuracy. Job Types: Full time, In office Internship Contract length: 3 months

Location: Bangalore Experience Level: 6-8 years Position: Lead Data Scientist Education: BE/BTech from Tier 1 institutes (IITs/IIITs/NITs). Preferably MS in CS/NLP/KGs/Vision at top tier institute, for lead DS. Reimagine Travel decisions with the power of AI @ MakeMyTrip. MakeMyTrip has been AI/ML/Data/Platform powered organization. We are now shaping the future of travel for Bharat customers, with GenAI-centric innovations, leveraging SLMs, Vernacular STT/TTS, and travel content systems. Join us to take these systems, chatbots, Cx, content to next orbit of excellence. About The Role As a Lead data scientist , you will: Design, develop, and fine-tune multilingual Small Language Models (SLMs) with advanced AI capabilities for agentic applications such as travel destination expertise, Myra bot orchestration, hotel semantic search, and customer support bot assistance. Build custom Natural Language Inference (NLI) and reward-scoring models to improve preference-based SLM training(DPO, PPO, SteerLM etc), enhancing multi-agent response quality and relevance. Develop and implement active learning pipelines for data and models, for NLP, Named Entity Recognition (NER), conversational latent intent/concepts, travel-specific embeddings, and domain-specific SLM training for summarization, rephrasing, and planning. Architect and enhance conversational AI systems to dynamically adapt and comprehend concepts/intents, NLP, and NER tasks across multiple lines of business, supporting the Myra chatbot ecosystem. Drive end-to-end quality assurance through robust integration and experience testing, establishing objective evaluation metrics and leveraging A/B testing for performance optimization. Mentor and guide engineering teams in advanced SLM and Generative AI analytics, fostering growth and innovation. Collaborate across teams to deliver scalable solutions that impact millions of users, ensuring alignment with business goals. Focus on hosting and deploying Generative AI models on robust and efficient infrastructure to support large-scale operations. What You Bring Deep experience in Natural Language Processing (NLP & NLI), tiny/small language models, base language model retraining (both transformer and BERT based architectures). Extensive experience in conversational NLP systems. Experience in SLM adaptor fine tuning, SFT training, SLM pruning (base and instruct models) Experience in retriever frameworks in Q&A bots. Experience in contrastive learning, graph learning based embedding methods with heterogenous features. Preferably experience in building NLP active learning pipelines. Demonstrable experience in scaling your models to large scale search systems is a plus. Very good critical reasoning skills, data centric NLP/NLI systems. Must have temperament and hunger to work in fast-paced environment. Why Join Us? Be part of a team revolutionizing the travel industry with cutting-edge AI and Generative AI technologies, impacting millions of users worldwide.

🚀 AI-FULL STACK INTERN → FUTURE TECH LEAD (MERN / PYTHON + DEVOPS) Location: Lucknow (Onsite) | Duration: 6 Months → Full-Time “For rebels who fine-tune Llama 3 before breakfast and argue about Kubernetes over chai. If deploying open-source models on Hetzner at 2 AM excites you—this is your battleground.” 💻 Your War Mission Build AI-powered business weapons that redefine industries: ⚔️ Deploy open-source giants : Llama 3, Mistral, Phi-3 — optimize for consultative salesbots, customer assistants, and predictive engines. ⚔️ Architect at scale : Melt cloud clusters (AWS/Hetzner/Runpod) with real-time RAG systems, then rebuild them cost-efficient. ⚔️ Lead like a hacker-general : Mentor squads, review PRs mid-deployment, and ship production-grade tools in 48-hour sprints. ⚔️ Bridge chaos to clarity : Turn founder visions into Python + React missiles — no red tape, just impact. ⚔️ Your Arsenal 🧑‍💻 Code Weapons Python (Flask, Django) Node.js / Express React / Next.js MongoDB / Postgres ☁️ Cloud & DevOps Gear AWS (Lambda, ECS) Hetzner Bare Metal Servers Runpod GPU Clusters Docker / Kubernetes CI/CD Pipelines 🧠 AI / ML Firepower OSS Models: Llama 3, Mistral, DeepSeek LangChain / LangGraph + custom RAG hacks HuggingFace Transformers Real-time inference tuning 🧠 Who You Are ✅ Code gladiator with 3+ real projects on GitHub (bonus if containers have escaped into prod). ✅ Cloud insurgent fluent in IaC (Infrastructure as Code) – Hetzner and Runpod are your playground. ✅ Model whisperer – you’ve fine-tuned, quantized, and deployed open weights in real battles. ✅ Startup DNA – problems are loot boxes, not blockers. Permission is for the weak. 💥 Why This Beats Corporate Internships 🔧 Tech Stack: MERN + Python + Open-source AI/DevOps fusion (rare combo!) 🚀 Real Impact: Your code goes live to clients – no “simulations” or shadow projects. 🧠 Full Autonomy: You’ll get access to GPU clusters + full architectural freedom. 📈 Growth Path: Fast-track to full-time with competitive compensation + equity. 💼 Culture: No red tape. Just shipping, solving, and high-fives. 🎯 The Deal Phase 1: Intern (0–6 Months) Fixed stipend (for the bold, not the comfy) Ship 2+ client-ready AI products (portfolio > pedigree) Master open-source model deployment at scale Phase 2: FTE (Post 6 Months) Competitive comp + meaningful equity Lead AI pods with cloud budget autonomy ⚡ Apply If You: Can optimize Llama 3 APIs on Hetzner while debugging K8s Believe open-source > closed models for real-world impact Treat “impossible deadlines” as power-ups Can start yesterday 📮 How to Apply Drop your GitHub link (show us your best OSS battle scars) Write a 1-sentence battle cry : “How I’d deploy Mixtral to crush customer support costs” Email us at: careers@foodnests.com Subject line: [OSS GLADIATOR] - {Your Name} - {Cloud War Story} “We don’t count years. We count models deployed at 3 AM.” (Top 10 GitHub profiles get early interviews) #HiringNow #AIInternship #FullStackIntern #OpenSourceAI #MERNStack #PythonDeveloper #DevOpsJobs #LangChain #Runpod #Kubernetes #GitHubHackers #StartupJobs #EngineeringGraduates #BTechLife #LifeAtStartup #NowHiring #HackAndLead #ProductMindset #FullStackLife #GPTDev #AIxEngineering #BuilderNotBystander #StartupTech #GrowthHack #NodejsJobs #PythonDev #AWSCloud #EngineeringLeadership #JaipurTech #MakeStuffReal

About the job What makes Techjays an inspiring place to work At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals who have honed their skills at leading companies such as Google, Akamai, NetApp, ADP, Cognizant Consulting, and Capgemini. With engineering teams across the globe, we deliver tailored AI software and services to clients ranging from startups to large-scale enterprises. Be part of a company that’s pushing the boundaries of digital transformation. At Techjays, you’ll work on exciting projects that redefine industries, innovate with the latest technologies, and contribute to solutions that make a real-world impact. Join us on our journey to shape the future with AI. We are looking for a detail-oriented and curious AI QA Engineer to join our growing QA team. You will play a critical role in ensuring the quality, safety, and reliability of our AI-powered products and features. If you're passionate about AI, testing complex systems, and driving high standards of quality—this role is for you! Primary Skills: QA Automation, Python, API Testing, AI/ML Testing, Prompt Evaluation, Adversarial Testing, Risk-Based Testing, LLM-as-a-Judge, Model Metrics Validation, Test Strategy. Secondary Skills: CI/CD Integration, Git, Cloud Platforms (AWS/GCP/Azure ML), MLFlow, Postman, Testim, Applitools, Collaboration Tools (Jira, Confluence), Synthetic Data Generation, AI Ethics & Bias Awareness. Experience: 3 - 8 Years Work Location: Coimbatore/ Remote Must-Have Skills: Foundational QA Skills Strong knowledge of test design, defect management, and QA lifecycle . Experience with risk-based testing and QA strategy. AI/ML Knowledge Basic understanding of machine learning workflows , training/inference cycles. Awareness of AI quality challenges : bias, fairness, transparency. Familiarity with AI evaluation metrics: accuracy, precision, recall, F1-score . Hands-on with prompt testing , synthetic data generation , and non-deterministic behavior validation. Technical Capabilities Python programming for test automation and data validation. Hands-on experience with API testing tools (Postman, Swagger, REST clients). Knowledge of test automation tools (e.g., PyTest , Playwright, Selenium). Familiarity with Git and version control best practices. Understanding of CI/CD pipelines and integration testing. Tooling (Preferred) Tools like Diffblue, Testim, Applitools, Kolena, Galileo, MLFlow, Weights & Biases . Basic understanding of cloud-based AI platforms (AWS Sagemaker, Azure ML, GCP Vertex AI). Soft Skills Excellent analytical thinking and attention to detail. Strong collaboration and communication skills to work across cross-functional teams. Proactive and pull-mode work ethic —self-starter who takes ownership. Passion for learning new technologies and contributing to AI quality practices. Roles & Responsibilities: Design, write, and execute test plans and test cases for AI/ML-based applications. Collaborate with data scientists, ML engineers, and developers to understand model behavior and expected outcomes. Perform functional, regression, and exploratory testing on AI components and APIs. Validate model outputs for accuracy, fairness, bias, and explainability . Implement and run adversarial testing , edge cases, and out-of-distribution data scenarios. Conduct prompt testing and evaluation for LLM (Large Language Model)-based applications. Use LLM-as-a-Judge and AI tools to automate evaluation of AI responses where possible. Validate data pipelines , datasets, and ETL workflows. Track model performance metrics such as precision, recall, F1-score , and flag potential degradation. Document defects, inconsistencies, and raise risks proactively with the team. What we offer: Best in packages Paid holidays and flexible paid time away Casual dress code & flexible working environment Medical Insurance covering self & family up to 4 lakhs per person. Work in an engaging, fast-paced environment with ample opportunities for professional development. Diverse and multicultural work environment Be part of an innovation-driven culture that provides the support and resources needed to succeed.

Role Summary We are looking for a passionate Python developer to work on football video and data analytics systems using computer vision and deep learning. Key Responsibilities Build pipelines for video ingestion, object tracking, and tactical data extraction Apply CV models to game scenarios (e.g., player recognition, heatmaps, motion vectors) Collaborate with football analysts to translate tactical needs into technical tools Requirements 3+ years of Python development experience Proficiency with OpenCV, PyTorch, TensorFlow, and real-time inference systems Familiarity with YOLO, segmentation models, sports analytics tools a big plus Strong passion for football and understanding of tactics, formations, and gameplay

Over 12 years of extensive experience in AI/ML , with a proven track record of architecting and delivering enterprise-scale machine learning solutions across the Retail and FMCG domains . Demonstrated ability to align AI strategy with business outcomes in areas such as customer experience, dynamic pricing, demand forecasting, assortment planning, and inventory optimization. Deep expertise in Large Language Models (LLMs) and Generative AI , including OpenAI’s GPT family , ChatGPT , and emerging models like DeepSeek . Adept at designing domain-specific use cases such as intelligent product search, contextual recommendation engines, conversational commerce assistants, and automated customer engagement using Retrieval-Augmented Generation (RAG) pipelines. Strong hands-on experience developing and deploying advanced ML models using modern data science stacks including: Python (advanced programming with focus on clean, scalable codebases) TensorFlow and Scikit-learn (for deep learning and classical ML models) NumPy , Pandas (for data wrangling, transformation, and statistical analysis) SQL (for structured data querying, feature engineering, and pipeline optimization) Expert-level understanding of Deep Learning architectures (CNNs, RNNs, Transformers, BERT/GPT), and Natural Language Processing (NLP) techniques such as entity recognition, text summarization, semantic search, and topic modeling – with practical application in retail-focused scenarios like product catalog enrichment, personalized marketing, and voice/text-based customer interactions. Strong data engineering proficiency , with experience designing robust data pipelines, building scalable ETL workflows, and integrating structured and unstructured data from ERP, CRM, POS, and social media platforms. Proven ability to operationalize ML workflows through automated retraining, version control, and model monitoring. Significant experience deploying AI/ML solutions at scale on cloud platforms such as AWS (SageMaker, Bedrock) , Google Cloud Platform (Vertex AI) , and Azure Machine Learning . Skilled in designing cloud-native architectures for low-latency inference, high-volume batch scoring, and streaming analytics. Familiar with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML (MLOps). Ability to lead cross-functional teams , translating technical concepts into business impact, and collaborating with marketing, supply chain, merchandising, and IT stakeholders. Comfortable engaging with executive leadership to influence digital and AI strategies at an enterprise level.

About Zupee We are the biggest online gaming company with largest market share in the Indian gaming sector’s largest segment — Casual & Boardgame. We make skill-based games that spark joy in the everyday lives of people by engaging, entertaining, and enabling earning while at play. In the three plus years of existence, Zupee has been on a mission to improve people’s lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from the stressful environments we live in today and sparks joy in the lives of people through its games. Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since Q3, 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India.. ABOUT THE JOB Role: Senior Machine Learning Engineer Reports to: Manager- Data Scientist Location: Gurgaon Experience: 3-6 Years Role & Responsibilities 1) Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. 2) Collaborate with ML teams to optimize models for inference performance, latency, and resource utilization. 3) Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. 4) Implement techniques such as model quantization, pruning, knowledge distillation, or hardware-specific optimizations (e.g., TensorRT, ONNX). 5) Architect, design, and develop reusable tools, libraries, and infrastructure to accelerate ML deployment and performance analysis for the broader organization. 6) Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. 7) Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. 8) Optimization of the queries and pipelines. Modernization of the applications whenever required. Must - Have Skills: 1) MlOps 2) Python 3) AWS 4) Bash 5) Kubernetes Desired Skills 1) Sagemaker 2) Triton 3) Nvidia 4) GPU 5) Model Optimization

100% ONSITE - 5 Days office - Sat & Sun Off Position: AI Developer Experience: 6 to 8 Years Location: Hyderabad (Mandatory) Work Mode: 5 Days Work from Office Key Responsibilities: Design, develop, and deploy AI-powered agents and intelligent automation solutions Work extensively with LLMs, NLP, and ML/DL frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers) Integrate AI solutions into enterprise systems and business processes using APIs and RPA tools like UiPath or Automation Anywhere Fine-tune and optimize pre-trained AI models focusing on scalability, accuracy, and performance Collaborate with cross-functional teams – Product, Data Engineering, DevOps, and Business Stakeholders Stay updated with the latest AI advancements and apply them to business solutions Maintain proper documentation and testing protocols for AI solutions Required Skills & Qualifications: 6–8 years of hands-on experience in AI development Expertise in: LLMs (GPT, BERT, LLaMA, etc.) ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) NLP techniques (classification, NER, summarization) RPA tools and AI integration Proficient in Python (must), and optionally Java/C++ Strong knowledge of fine-tuning, prompt engineering, and inference optimization Excellent problem-solving and cross-functional communication skills Powered by JazzHR DFusY9IqqR

Job Description: Senior MLOps Engineer Position: Senior MLOps Engineer Location: Gurugram Relevant Experience Required: 6+ years Employment Type: Full-time About The Role We are seeking a Senior MLOps Engineer with deep expertise in Machine Learning Operations, Data Engineering, and Cloud-Native Deployments . This role requires building and maintaining scalable ML pipelines , ensuring robust data integration and orchestration , and enabling real-time and batch AI systems in production. The ideal candidate will be skilled in state-of-the-art MLOps tools , data clustering , big data frameworks , and DevOps best practices , ensuring high reliability, performance, and security for enterprise AI workloads. Key Responsibilities MLOps & Machine Learning Deployment Design, implement, and maintain end-to-end ML pipelines from experimentation to production. Automate model training, evaluation, versioning, deployment, and monitoring using MLOps frameworks. Implement CI/CD pipelines for ML models (GitHub Actions, GitLab CI, Jenkins, ArgoCD). Monitor ML systems in production for drift detection, bias, performance degradation, and anomaly detection. Integrate feature stores (Feast, Tecton, Vertex AI Feature Store) for standardized model inputs. Data Engineering & Integration Design and implement data ingestion pipelines for structured, semi-structured, and unstructured data. Handle batch and streaming pipelines with Apache Kafka, Apache Spark, Apache Flink, Airflow, or Dagster. Build ETL/ELT pipelines for data preprocessing, cleaning, and transformation. Implement data clustering, partitioning, and sharding strategies for high availability and scalability. Work with data warehouses (Snowflake, BigQuery, Redshift) and data lakes (Delta Lake, Lakehouse architectures). Ensure data lineage, governance, and compliance with modern tools (DataHub, Amundsen, Great Expectations). Cloud & Infrastructure Deploy ML workloads on AWS, Azure, or GCP using Kubernetes (K8s) and serverless computing (AWS Lambda, GCP Cloud Run). Manage containerized ML environments with Docker, Helm, Kubeflow, MLflow, Metaflow. Optimize for cost, latency, and scalability across distributed environments. Implement infrastructure as code (IaC) with Terraform or Pulumi. Real-Time ML & Advanced Capabilities Build real-time inference pipelines with low latency using gRPC, Triton Inference Server, or Ray Serve. Work on vector database integrations (Pinecone, Milvus, Weaviate, Chroma) for AI-powered semantic search. Enable retrieval-augmented generation (RAG) pipelines for LLMs. Optimize ML serving with GPU/TPU acceleration and ONNX/TensorRT model optimization. Security, Monitoring & Observability Implement robust access control, encryption, and compliance with SOC2/GDPR/ISO27001. Monitor system health with Prometheus, Grafana, ELK/EFK, and OpenTelemetry. Ensure zero-downtime deployments with blue-green/canary release strategies. Manage audit trails and explainability for ML models. Preferred Skills & Qualifications Core Technical Skills Programming: Python (Pandas, PySpark, FastAPI), SQL, Bash; familiarity with Go or Scala a plus. MLOps Frameworks: MLflow, Kubeflow, Metaflow, TFX, BentoML, DVC. Data Engineering Tools: Apache Spark, Flink, Kafka, Airflow, Dagster, dbt. Databases: PostgreSQL, MySQL, MongoDB, Cassandra, DynamoDB. Vector Databases: Pinecone, Weaviate, Milvus, Chroma. Visualization: Plotly Dash, Superset, Grafana. Tech Stack Orchestration: Kubernetes, Helm, Argo Workflows, Prefect. Infrastructure as Code: Terraform, Pulumi, Ansible. Cloud Platforms: AWS (SageMaker, S3, EKS), GCP (Vertex AI, BigQuery, GKE), Azure (ML Studio, AKS). Model Optimization: ONNX, TensorRT, Hugging Face Optimum. Streaming & Real-Time ML: Kafka, Flink, Ray, Redis Streams. Monitoring & Logging: Prometheus, Grafana, ELK, OpenTelemetry.

Position Overview: Here at ShyftLabs, we are looking for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system, and provide a data-driven insight and scientific solution. ShyftLabs is a growing data product company that was founded in early 2020, and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation. Job Responsibilities: Data Analysis and Research: Analyzing a large dataset with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could complete and improve a complex ML and bidding system Simulation and Modelling: Validating and quantifying the efficiency and performance gain from hypotheses through rigorous simulation and modelling Experimentation and Causal Inference: Developing a robust experiment design and metric framework, and providing reliable and unbiased insights for product and business decision making Basic Qualifications: Master's degree in a quantitative discipline or equivalent 3+ years minimum professional experience Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets and using statistics to arrive at a recommendation Excellent verbal and written communication skills, with the ability to present information and analysis results effectively Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company Statistics: Must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models Machine Learning: Must have a deep understanding of ML algorithms (i.e., deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and their development, validation, and evaluation Programming: Experience with Python, R, or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas) We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Position Title Manager - Deployment, Service and Replenishment Function/Group Logistics Location Mumbai Shift Timing 3.30 pm to 12.30 am Role Reports to Sr Manager - Deployment, Replenishment and Service Remote/Hybrid/in-Office Hybrid: Currently 2 days in a week but need to adhere if it changes in future. Over and above days defined in hybrid, need to be in office for additional days as per business requirements. About General Mills We make food the world loves: 100 brands. In 100 countries. Across six continents. With iconic brands like Cheerios, Pillsbury, Betty Crocker, Nature Valley, and Häagen-Dazs, we’ve been serving up food the world loves for 155 years (and counting). Each of our brands has a unique story to tell. How we make our food is as important as the food we make. Our values are baked into our legacy and continue to accelerate us into the future as an innovative force for good. General Mills was founded in 1866 when Cadwallader Washburn boldly bought the largest flour mill west of the Mississippi. That pioneering spirit lives on today through our leadership team who upholds a vision of relentless innovation while being a force for good. For more details check out http://www.generalmills.com General Mills India Center (GIC) is our global capability center in Mumbai that works as an extension of our global organization delivering business value, service excellence and growth, while standing for good for our planet and people. With our team of 1800+ professionals, we deliver superior value across the areas of Supply chain (SC) , Digital & Technology (D&T) Innovation, Technology & Quality (ITQ), Consumer and Market Intelligence (CMI), Sales Strategy & Intelligence (SSI) , Global Shared Services (GSS) , Finance Shared Services (FSS) and Human Resources Shared Services (HRSS).For more details check out https://www.generalmills.co.in We advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow. Job Overview Function Overview The GIC Supply Chain team manages end-to-end operations, encompassing planning, sourcing, manufacturing, logistics, and analytics. They strategically plan to meet market demands, optimize sourcing, ensure efficient production, and oversee the seamless movement of goods from production to delivery. The team employs advanced analytics throughout these processes, fostering adaptability and operational excellence. This collaborative approach ensures a well-coordinated supply chain that aligns with both organizational goals and dynamic market conditions. Link Purpose of the role General Mills India team virtually caters to multiple plants, warehouses, and several business teams / groups in US. The primary role will include people management, service management along with replenishment & network management responsibilities. The incumbent will drive collaboration between Distribution, Supply, demand planning, and System governance teams to achieve functional/organizational targets. The objective of this role is to drive efficiencies in case-fill while balancing cost and operational constraints. Lead and develop a team of distribution planners to achieve organizational goals. Support short-term replenishment strategies in collaboration with US replenishment managers. The Manager will collaborate with other planning teams (Demand/Supply) to proactively call-out service risks and minimize the impact on overall case-fill targets. Key Accountabilities Strategic responsibilities Ensure smooth supply chain distribution planning of finished goods for the assigned Operating Unit/s by meeting and exceeding KPI metrics (ex-Case fill rates) while optimizing overall SCM costs (transportation/inventory $). Accountable for tactical deployment decision-making for assigned OU and Deployment Process Governance. Acts as a Regional Replenishment lead supporting US Replenishment Managers in the creation and execution of short-term execution of network strategies identified. Support Deployers and Network SPOCs in problem-solving and decision-making related to operational and network constraints (Transportation, Warehouse, Plant Outbound, and Network space) Operational Responsibilities Develop knowledge and expertise in General Mills planning systems (SAP R/3, OMP, Inventory Analyst, Terra DS etc.) Provide regular communication updates on key performance metrics (case fill goals, service issues, inventory targets, warehouse/transportation constraints etc.) to the business stakeholders. Collaborate across supply chain teams (DP, scheduling, Customer service, warehousing, transportation, plants etc.) to identify and implement information and product flow improvements driving better Service for the OU Ensure execution as per standard processes and documentation. Utilize Continuous Improvement (CI) tools to drive process improvements. Actively participate in Staff meetings, Knowledge sharing sessions, Trainings, Collaboration meetings etc. Accountable for Distribution Planning Systems/Tools (OMP/Tableau dashboard/ERP) utilization sustainability Drive Run, Improve, and Transform methodologies. Projects Work on cross functional projects Lead organization/Function level initiatives to drive efficiencies and cost savings. Participate and contribute to Goal/ objective setting process for the fiscal year. Continuous Improvement Build Architectural solutions through Automation, Standardization, Lean approach etc. Build sustainable and order winning solutions for the problems. Collaborate across with various team to implement defined solutions. Develop and implement repeatable and scalable models. Perform external competitive benchmarking and analysis. Lead Cost savings initiatives Lead ideation and drive implementation to deliver organizational goals. Develop sustainable tools for the capabilities. Continue Professional Career Development Participate in soft skills training driven by L&D Team Leveraging Future skills & Supply chain university platform to explore the emerging technologies & enhance Supply chain skills People Responsibilities Participate in developing goals and objectives for the Fiscal Year Energize and develop people by collaborating across boundaries. Train and Coach team members Complete annual performance management processes (annual objective setting, performance assessment and reviews, IDP, etc.) Hire, retain, and develop team members ensuring flawless execution of responsibilities without any disruption to the business. Organizational Effectiveness Identify collaboration opportunities across subgroups and beyond Deployment team. Share best practices / learnings with SME’s. Support development and Transition of new capabilities across Distribution planning organization Minimum Qualification Full Time graduation from an accredited university (Mandatory) Related experience: Bachelors (8 years); MBA (6+ years) Supply chain knowledge (Core Distribution Planning & Logistic Operation, Basic logistic planning) Systems (SAP/OMP) understanding. Demonstrated Strong Project Management skills. Forward thinker and self-motivator that thrives on new challenges and adapts quickly to learning new knowledge. Continuous improvement mindset Strategic and Tactical decision making Critical Thinking and Analytical Skills Data Visualization and Storytelling Strong Stakeholder Management and Influencing Skills Strong analytical skills to draw inference and provide meaningful insights. Ability to translate Business information into actionable information. Excel and analysis skills (i.e., skilled at pivot table, charts / graphs, macros, solver, queries, mathematical functions etc.) Strong mathematical skills. Statistical skills will carry additional weightage. Exposure / experience of working with various- ERP systems (OMP/SAP/O9) and Supply Chain and Reporting tools (Inventory Analyst, Tableau etc.) Team Development Ability to benchmark / conduct external research for the capability and process. Ability to execute, multi-task and deliver on commitments. Can prioritize and complete multiple tasks on tight deadlines. Coaching and Mentoring Ability to connect the dots and navigate through ambiguous situations. Excellent understanding of Supply Chain concepts, inventory management concepts and tools. Proven self-management and time management skills. Excellent communication (verbal & written) and presentation skills. Proactive and solution-oriented approach along with ability to influence. Critical thinking ability to understand granularity of the situation / problem. Ability and agility to navigate through change. Preferred Qualification Master’s degree 6-7 years of related experience Major Area of Study in Supply Chain Preferred Professional Certifications: APICS – CSCP, PMP, Six Sigma

Title: Platform Architect — GenAI/LLM Systems Location: Hyderabad Experience: 7+ Years Employment Type: Full-Time | Immediate Start About the Role We are seeking a skilled and passionate Platform Architect – GenAI/ LLM Systems to join our team. What You’ll Do Architect scalable, cloud-native infrastructure to support enterprise-grade GenAI and LLM-powered applications. Design and deploy secure, reliable API gateways, orchestration layers (Airflow, Kubeflow), and CI/CD workflows for ML and LLM pipelines Collaborate with data and ML engineering teams to enable low-latency LLM inference and vector-based search platforms across GCP (or multi-cloud) Define and implement a semantic layer and data abstraction strategy to enable consistent and governed consumption of data across LLM and analytics use cases. Implement robust data governance frameworks including role-based access control (RBAC), data lineage, cataloging, observability, and metadata management. Guide architectural decisions around embedding stores, vector databases, LLM tooling, and prompt orchestration (e.g., LangChain, LlamaIndex) Establish compliance and security standards to meet enterprise SLA, privacy, and auditability requirements. What Sets You Apart 7+ years of experience as a Platform/Cloud/Data Architect, ideally within GenAI, Data Platforms, or LLM systems. Strong cloud infrastructure experience on GCP (preferred), AWS, or Azure, including Kubernetes, Docker, Terraform/IaC. Demonstrated experience building and scaling LLM-powered architectures using OpenAI, Vertex AI, LangChain, LlamaIndex, etc. Familiarity with semantic layers, data catalogs, lineage tracking, and governed data delivery across APIs and ML pipelines. Track record of deploying production-grade GenAI/LLM services that meet performance, compliance, and enterprise integration requirements. Strong communication and cross-functional leadership skills — ability to translate business needs into scalable architecture

Location: Hybrid/ Remote Type: Contract / Full‑Time Experience: 5+ Years Qualification: Bachelor’s or Master’s in Computer Science or a related technical field Responsibilities Architect & implement the RAG pipeline: embeddings ingestion, vector search (MongoDB Atlas or similar), and context-aware chat generation. Design and build Python‑based services (FastAPI) for generating and updating embeddings. Host and apply LoRA/QLoRA adapters for per‑user fine‑tuning. Automate data pipelines to ingest daily user logs, chunk text, and upsert embeddings into the vector store. Develop Node.js/Express APIs that orchestrate embedding, retrieval, and LLM inference for real‑time chat. Manage vector index lifecycle and similarity metrics (cosine/dot‑product). Deploy and optimize on AWS (Lambda, EC2, SageMaker), containerization (Docker), and monitoring for latency, costs, and error rates. Collaborate with frontend engineers to define API contracts and demo endpoints. Document architecture diagrams, API specifications, and runbooks for future team onboarding. Required Skills Strong Python expertise (FastAPI, async programming). Proficiency with Node.js and Express for API development. Experience with vector databases (MongoDB Atlas Vector Search, Pinecone, Weaviate) and similarity search. Familiarity with OpenAI’s APIs (embeddings, chat completions). Hands‑on with parameters‑efficient fine‑tuning (LoRA, QLoRA, PEFT/Hugging Face). Knowledge of LLM hosting best practices on AWS (EC2, Lambda, SageMaker). Containerization Skills (Docker) Good understanding of RAG architectures, prompt design, and memory management. Strong Git workflow and collaborative development practices (GitHub, CI/CD). Nice‑to‑Have Experience with Llama family models or other open‑source LLMs. Familiarity with MongoDB Atlas free tier and cluster management. Background in data engineering for streaming or batch processing. Knowledge of monitoring & observability tools (Prometheus, Grafana, CloudWatch). Frontend skills in React to prototype demo UIs. Skills:- Artificial Intelligence (AI), Generative AI, Python, NodeJS (Node.js), Vector database, Amazon Web Services (AWS), Docker, Retrieval Augmented Generation (RAG) and CI/CD

At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives. Those in Guidewire testing at PwC will specialise in testing and quality assurance activities related to Guidewire applications. Guidewire is a software suite that provides insurance companies with tools for policy administration, claims management, and billing. You will be responsible for confirming that the Guidewire applications meet the desired quality standards and perform as expected. Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Apply a learning mindset and take ownership for your own development. Appreciate diverse perspectives, needs, and feelings of others. Adopt habits to sustain high performance and develop your potential. Actively listen, ask questions to check understanding, and clearly express ideas. Seek, reflect, act on, and give feedback. Gather information from a range of sources to analyse facts and discern patterns. Commit to understanding how the business works and building commercial awareness. Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills Skill - GW Testing - Associate Total Experience – 2 - 5 years Edu Qualification: BTech/BE/MTech/MS/MCA Job Description - Reviewing requirements / specifications / technical design documents Designing detailed, comprehensive and well-structured Test Plans and Test Cases Setting up Test Environment & Test Data Executing tests as needed throughout the project. Analyzing and reporting test results. Identifying and tracking defects through their lifecycle. Understanding of Integration - Technical Design Document and Use Case Testing experience of any one of the Guidewire products: Policy center Experience on policy transactions, workflow ,Audits, forms inference Performing thorough testing [Smoke / System / Integration / Regression / Stabilization Possessing expertise in Test Management Tools like ALM / Jira

Job Title: AI/ML Validation Engineer Location: Bangalore (Onsite) Experience: 5-8 yrs Requirements: · Strong background in machine learning fundamentals, including deep learning,large language models, and recommender systems. · Strong background in validation, defect and software development life cycle · Strong knowledge on ubuntu / yocto linux · Experience working with opensource frameworks such as PyTorch, TensorFlow, and ONNX-Runtime. · Experience in profiling ML workloads · Prior experience in executing validation plans for AI/ML compute stacks such as HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime and TensorFlow/PyTorch integrations. · Prior experience in validating end-to-end AI pipelines, for e.g. model conversion (e.g., PyTorch à ONNX), Inference runtimes (e.g, ONNX Runtime, TensorRT, ROCm/HIP), compilers/toolchains (e.g. TVM, Vitis AI, XDNA, XLA), kernel execution, memory transfer and inference results · Strong background in python programming. · Excellent problem-solving skills and willingness to think outside the box. · Experience with production software quality assurance practices, methodologies, and procedures · Strong ownership of deliverables, Excellent communication skills and experience working with global teams

Job Description Role: Manager - Data Analytics Location: New Delhi Chegg provides individualized learning support to students as they pursue their educational journeys. Available on demand 24/7 and powered by over a decade of learning insights, the Chegg platform offers students AI-powered academic support thoughtfully designed for education coupled with access to a vast network of subject matter experts who ensure quality. No matter the goal, level, or style, Chegg helps millions of students around the world learn with confidence by helping them build essential academic, life, and job skills to achieve success. Your analysis will provide valuable insights and identify key levers that materially improve how and what we create, as well as how we manage and deliver our content. Strong communication and analytic skills are critical for success in this role. Curiosity, persistence, creativity, and a desire to understand “the why” will make you successful in this role. Role Overview: As a Manager – Data Analytics, you will lead a high-impact analytics team. With a strategic mindset and a strong technical foundation, you’ll drive data-informed decision-making, lead cross-functional projects, and build scalable analytical solutions to shape Chegg’s future. You’ll be responsible for leading and mentoring Data analysts, designing robust analytical frameworks, and engaging with senior stakeholders to inform key business decisions. This role demands strong leadership, deep analytical expertise, and excellent communication skills. Key Responsibilities: Lead a team of analysts to deliver impactful insights across product, operations, and customer engagement. Develop and scale advanced analytical models to inform business strategy, product development, and customer experience. Own end-to-end project execution: from problem definition and data sourcing to insight generation and stakeholder presentation. Collaborate with product, engineering, marketing, and operations leaders to drive data-driven decisions across the company. Monitor KPIs and performance metrics to track success of initiatives and proactively identify areas for improvement. Mentor the team in using advanced tools (e.g., Python, SQL, Tableau, Amplitude) to create dashboards, reports, and predictive models. Influence data instrumentation decisions to ensure robust tracking and data quality. Evangelize data literacy across teams and foster a culture of curiosity, experimentation, and continuous learning. Qualifications: 10+ years of experience in analytics, with at least 3+ years in a leadership or managerial role. Proven experience in building and scaling analytics teams and processes. Master’s degree preferred (in Statistics, Mathematics, Engineering, Economics, or a related field). Strong expertise in Python (mandatory), SQL, and BI tools like Tableau, Databricks, or PowerBI. Hands-on experience with forecasting models, statistical inference, and predictive modeling techniques. Deep understanding of data infrastructure, experimentation frameworks (A/B testing), and data governance. Experience with APIs, JSON data structures, and product analytics tools like Amplitude or Mixpanel. Excellent communication and storytelling skills; ability to simplify complex data into actionable business insights. Strategic thinker with a problem-solving mindset and a Why do we exist? Students are working harder than ever before to stabilize their future. Our recent research study called State of the Student shows that nearly 3 out of 4 students are working to support themselves through college and 1 in 3 students feel pressure to spend more than they can afford. We founded our business on provided affordable textbook rental options to address these issues. Since then, we’ve expanded our offerings to supplement many facets of higher educational learning through Chegg Study, Chegg Math, Chegg Writing, Chegg Internships, Thinkful Online Learning, and more to support students beyond their college experience. These offerings lower financial concerns for students by modernizing their learning experience. We exist so students everywhere have a smarter, faster, more affordable way to student. About Us What is Chegg? An ‘always on’ digital learning platform. Chegg puts students first…Everything we build in this company is student-focused, making us the leading student-first connected learning platform. Chegg strives to improve the overall return on investment in education by helping students learn more in less time and at a lower cost. This is achieved by providing students a multitude of educational tools from affordable textbook rentals to Chegg Study which supplements their learning through 24/7 tutor access, step-by-step help with questions, and more. Chegg is a publicly-held company based in Santa Clara, California and trades on the NYSE under the symbol CHGG.

We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and deployment of advanced AI systems. You will work on cutting-edge machine learning models, natural language processing, computer vision, and AI infrastructure to solve real-world problems and drive innovation across our products and services. Key Responsibilities: Design, develop, and deploy scalable AI/ML models for production environments. Lead end-to-end AI project lifecycles from data collection and preprocessing to model training, evaluation, and deployment. Collaborate with cross-functional teams including data scientists, software engineers, and product managers. Optimize model performance and ensure robustness, fairness, and explainability. Stay current with the latest research and advancements in AI and machine learning. Mentor junior engineers and contribute to building a strong AI engineering culture. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (PhD preferred). 5+ years of experience in AI/ML engineering with a strong portfolio of deployed models. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc. Experience with cloud platforms (AWS, Azure) and MLOps tools. Strong understanding of data structures, algorithms, and software engineering principles. Excellent problem-solving and communication skills. Preferred Qualifications: Experience with LLMs, RAG, or agentic AI (Crew AI) systems. Familiarity with vector databases, prompt engineering, and AI safety practices. Contributions to open-source AI projects or published research papers. Experience with real-time inference systems and edge AI.

Senior Software Engineer Bangalore, Karnataka, India Date posted Jul 28, 2025 Job number 1849823 Work site Up to 50% work from home Travel 0-25 % Role type Individual Contributor Profession Software Engineering Discipline Software Engineering Employment type Full-Time Overview Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission. As Microsoft's cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the SW/FW Centre of Excellence team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for seasoned engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure. We are looking for a highly motivated Senior Software Engineer with a track record in Cloud Service development to come help us develop and light up innovative AI-based solutions to improve engineering efficiency across development, validation and monitoring. To be successful in this role, you must have a great track record of delivering quality results to customers, an engineering mindset, an innate aptitude for agility, and technical excellence in software engineering. #SCHIE Qualifications Required Qualifications Bachelor’s degree in Computer Science, Computer Engineering, or a related field. 6+ years of industry experience in AI/ML engineering using platforms and languages/frameworks such as Python, Semantic Kernel, AutoGen, Azure AI Foundry, Mem0, Azure AI Search. Proven experience in designing, building, and deploying AI agents across the autonomy spectrum—from retrieval-based to task-oriented and autonomous agents. Strong background in developing web applications and services that integrate AI/ML models for business insights and automation. Preferred Qualifications Hands-on experience with large language models (LLMs), including training, fine-tuning, and inference optimization for multi-billion parameter models. Familiarity with the full ML lifecycle: data engineering, model training, evaluation, deployment, and monitoring. Understanding of embedded systems, firmware development, OS concepts is a strong plus. Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter. Responsibilities Design and implement AI agents using modern agent development frameworks (e.g., Semantic Kernel, AutoGen, AI Foundry). Build scalable, production-grade AI services that integrate with enterprise systems and workflows. Collaborate with cross-functional teams to define agent capabilities, communication protocols, and compliance requirements. Optimize agent performance for real-time inference and continuous learning. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Information Industry Health Care Salary 0 - 3 K Date Opened 07/28/2025 Job Type Full time Work Experience 1-3 years City Bangalore North State/Province Karnataka Country India Zip/Postal Code 560048 Job Description Job Description: AI/ML Engineer Key Responsibilities Design, develop, and deploy deep learning and machine learning models, particularly convolutional neural networks (CNNs) for medical image analysis. Build scalable and efficient training and inference pipelines using frameworks like TensorFlow and PyTorch. Manage and deploy DL/ML solutions using local virtual machines (VMs); experience with cloud platforms like AWS and Azure is a plus. Containerize DL/ML workflows using Docker and implement CI/CD pipelines for model delivery. Optimize models for accuracy and speed; conduct A/B testing and validation with real-world radiology data. Collaborate with radiologists and software teams to integrate AI models into teleradiology platforms. Develop and maintain API integrations, including FastAPI-based services and interoperability with legacy systems. Monitor and maintain deployed models to ensure consistent performance in clinical environments. Requirements Must-Have Skills Proficient in Deep Learning and Machine Learning techniques. Strong experience with TensorFlow and PyTorch. Solid background in image processing and computer vision, especially with CNN architectures. Proficiency with Docker and experience with CI/CD pipelines. Excellent programming skills in Python and experience with relevant ML libraries. Understanding of data pipelines and handling large-scale medical imaging datasets. Nice to Have Experience deploying ML models on cloud platforms such as AWS and Azure. Experience with Kubernetes or orchestration frameworks. Familiarity with MLOps tools and workflows. Experience with distributed training or federated learning. Contributions to healthcare AI research or open-source projects. Education & Experience Bachelor’s or Master’s degree in Computer Science, Biomedical Engineering, Data Science, or related field. 1+ years of experience building and deploying machine learning solutions in production, preferably in a healthcare or radiology setting. Why Join Us? Opportunity to work on transformative AI applications in healthcare and radiology. Collaborative and mission-driven team environment. Access to advanced medical imaging datasets. Interested can apply to nanda.k@telradsol.com

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Java, Node, Deployment, Image Processing, AWS, Computer Vision, object detection, FastAPI Crop.Photo is Looking for: We’re looking for a hands-on engineering lead to own the delivery of our GenAI-centric product from the backend up to the UI — while integrating visual AI pipelines built by ML engineers. You’ll be both a builder and a leader: writing clean Python, Java and TypeScript, scaling AWS-based systems, mentoring engineers, and making architectural decisions that stand the test of scale. You won’t be working in a silo — this is a role for someone who thrives in fast-paced, high-context environments with product, design, and AI deeply intertwined. (Note: This role requires both technical mastery and leadership skills - we're looking for someone who can write production code, make architectural decisions, and lead a team to success.) What You’ll Do Lead development of our Java, Python (FastAPI), and Node.js backend services on AWS Deploy ML pipelines (built by the ML team) into containerized inference workflows using FastAPI, Docker, and GPU-enabled ECS EC2. Deploy and manage services on AWS ECS/Fargate, Lambda, API Gateway, and GPU-powered EC2 Contribute to React/TypeScript frontend when needed to accelerate product delivery Work closely with the founder, product, and UX team to translate business needs into working product Make architecture and infrastructure decisions — from media processing to task queues to storage Own the performance, reliability, and cost-efficiency of our core services Hire and mentor junior/mid engineers over time Drive technical planning, sprint prioritization, and trade-off decisions A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Skills & Experience We Expect Core Engineering Experience 6–8 years of professional software engineering experience in production environments 2–3 years of experience leading engineering teams of 5+ engineers Cloud Infrastructure & AWS Expertise (5+ years) Deep experience with AWS Lambda, ECS, and container orchestration tools Familiarity with API Gateway and microservices architecture best practices Proficient with S3, DynamoDB, and other AWS-native data services CloudWatch, X-Ray, or similar tools for monitoring and debugging distributed systems Strong grasp of IAM, roles, and security best practices in cloud environments Backend Development (5–7 years) Java: Advanced concurrency, scalability, and microservice design Python: Experience with FastAPI, building production-grade MLops pipelines Node.js & TypeScript: Strong backend engineering and API development Deep understanding of RESTful API design and implementation Docker: 3+ years of containerization experience for building/deploying services Hands-on experience deploying ML inference pipelines (built by ML team) using Docker, FastAPI, and GPU-based AWS infrastructure (e.g., ECS, EC2) — 2+ years System Optimization & Middleware (3–5 years) Application performance optimization and AWS cloud cost optimization Use of background job frameworks (e.g., Celery, BullMQ, AWS Step Functions) Media/image processing using tools like Sharp, PIL, Imagemagick, or OpenCV Database design and optimization for low-latency and high-availability systems Frontend Development (2–3 years) Hands-on experience with React and TypeScript in modern web apps Familiarity with Redux, Context API, and modern state management patterns Comfortable with modern build tools, CI/CD, and frontend deployment practices System Design & Architecture (4–6 years) Designing and implementing microservices-based systems Experience with event-driven architectures using queues or pub/sub Implementing caching strategies (e.g., Redis, CDN edge caching) Architecting high-performance image/media pipelines Leadership & Communication (2–3 years) Proven ability to lead engineering teams and drive project delivery Skilled at writing clear and concise technical documentation Experience mentoring engineers, conducting code reviews, and fostering growth Track record of shipping high-impact products in fast-paced environments Strong customer-centric and growth-oriented mindset, especially in startup settings — able to take high-level goals and independently drive toward outcomes without requiring constant handoffs or back-and-forth with the founder Proactive in using tools like ChatGPT, GitHub Copilot, or similar AI copilots to improve personal and team efficiency, remove blockers, and iterate faster How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

About the Role We are looking for a LLM (Large Language Models) Engineer to design, build, and optimize intelligent agents powered by Large Language Models (LLMs). You will work on cutting-edge AI applications , pre-train LLMs, fine-tune open-source models, integrate multi-agent systems, and deploy scalable solutions in production environments. Key Responsibilities – (Must Have) Develop and fine-tune LLM-based modesl and AI agents for automation, reasoning, and decision-making. Build multi-agent systems that coordinate tasks efficiently. Design prompt engineering, retrieval-augmented generation (RAG), and memory architectures . Optimize inference performance and reduce hallucinations in LLMs. Integrate LLMs with APIs, databases, and external tools for real-world applications . Implement reinforcement learning with human feedback (RLHF) and continual learning strategies. Collaborate with research and engineering teams to enhance model capabilities. Requirements 1+ years in AI/ML, with at least 1+ years in LLMs, or AI agents . Strong experience in Python, LangChain, LlamaIndex, Autogen, Hugging Face, etc. Experience with open-source LLMs (LLaMA, Mistral, Falcon, etc.) . Hands-on experience in LLM deployments with strong inference capabilities using robust frameworks such as vLLM. building multi-modal RAG systems. Knowledge of vector databases (FAISS, Chroma) for retrieval-based systems. Experience with LLM fine-tuning, downscaling, prompt engineering, and model inference optimization . Familiarity with multi-agent systems, cognitive architectures, or autonomous AI workflows . Expertise in cloud platforms (AWS, GCP, Azure) and scalable AI deployments . Strong problem-solving and debugging skills. Nice to Have Contributions to AI research, GitHub projects, or open-source communities . Experience with open-source LLMs (LLaMA, Mistral, Falcon, etc.) . Knowledge of Neural Symbolic AI, AutoGPT, BabyAGI, or similar frameworks . Job Type: Full-time Pay: ₹23,671.07 - ₹55,229.87 per month Benefits: Paid sick time Provident Fund Work Location: In person