Ai Algorithms Specialist in India

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Minimum experience of 4-6 Years required in AI ML Ops Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance

Role Summary The AI Knowledge Analyst is a member of the Customer Care and Managed Services team, responsible for ensuring the knowledge ecosystems that power GHX's operations and AI platforms are accurate, well-governed, and continuously improving. This role works closely with leadership, SMEs, data scientists, and operational teams to identify content gaps, manage knowledge lifecycles, and translate business needs into structured, AI-ready information assets. The AI Knowledge Analyst is equally comfortable working through a detailed content audit and presenting a structured recommendation to leadership. Strong organizational skills, clear communication, and a bias for action are required. This is a role for someone who treats knowledge gaps as solvable problems and can move from gap identification to resolution with minimal direction. Core Focus Areas Knowledge Governance & Lifecycle Management Maintain, organize, and govern the knowledge assets that support Customer Care and Managed Services teams. This includes managing intake, triage, and routing of knowledge requests; driving SME review cycles; and ensuring content is accurate, current, and ready for both human use and AI ingestion. AI Knowledge Readiness Identify, structure, and groom content that feeds GHX's AI platform. Partner with AI and data teams to ensure knowledge assets are formatted, accurate, and optimized for ingestion. Monitor AI solution performance and drive content improvements that translate into measurable efficiency gains. Roles & Responsibilities Knowledge Management & Content Quality Manage the intake, triage, and routing of knowledge-related requests from operational teams. Maintain content lifecycle through SME review checkpoints — flagging material for update, review, or archival on a consistent cadence. Identify obsolete, duplicate, or conflicting content and drive resolution through appropriate stakeholders. Conduct knowledge audits and implement improvement c

Job Details: Job Description: Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders. Responsibilities 1. Architect and develop Intel's reusable AI platform for Design Quality and Reliability. 2. Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation. 3. Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation. 4. Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools. 5. Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components. 6. Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability. 7. Implement human approval, deterministic validation, and rollback controls for consequential engineering actions. 8.

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity AI is a top strategic priority for New Relic, and the Bengaluru design team is at the center of it. The team works across three closely related product clusters: autonomous incident response (SRE Agent, Autopilot, and Intelligent RCA), the intelligence and platform layer that powers them (Ground Truth, Agentic Platform, and New Relic AI), and AIOps for event correlation and incident management. These products share a common design challenge: users need to trust systems that act autonomously, and building that trust through good design is genuinely hard work. This is an on-site role in Bengaluru. Your designers are there, and many of your engineering and product partners are too. Being present — in standups, reviews, and the quick conversations before a decision gets made — is part of how you'll build the relationships that make design effective. You'll also collaborate with design, product, and engineering partners in the US and Spain, so operating across time zones and communicating well in writing are part of the job. You'll manage a small team of designers and own the quality of the work across these products. The design questions here don't have established answers — how do you make an autonomous system legible? How do you build user trust in AI-generated root cause analysis? How do you design a handoff from machine decision to human judgment? If you're already working in AI product design, or actively building toward it, and you want to lead a team

Want to be a bswifter? At bswift we’ve been transforming benefits administration since 1996, making it simpler, smarter, and more human. Our state-of-the-art, cloud-based technology and services empower employees to understand, manage, and love their benefits. From downtown Chicago, and remotely across the country, we serve thousands of companies and millions of people nationwide, reducing administrative burdens and freeing HR teams to focus on creating thriving, people-first workplaces. We’re looking for motivated and goal-driven individuals who share our passion for delivering excellence and creating solutions that make a difference. The reward is a fun, flexible and creative environment with ample opportunity for professional and personal growth. If you love the bswift values of pursue excellence, embrace accountability, deliver superior service, and be a great place to work, we want to hear from you! About the Role We are looking for an AI Engineer II to design, build, and deploy cutting-edge generative AI applications , including agentic workflows and intelligent chat experiences , that transform how employees interact with their benefits. This role goes beyond individual contribution—you will own complex AI features end-to-end , influence architecture decisions around LLMs and agent systems , and mentor junior engineers . You will play a key role in bringing secure, scalable, and high-performance AI solutions to production using AWS cloud technologies. You will collaborate closely with software engineers, architects, product managers, and cross-functional teams to deliver seamless and impactful user experiences Key Responsibilities 1. Solution Design & Development Lead the design and development of scalable, secure, and high-performance applications . Architect robust backend systems and integrate them with frontend applications and third-party services. Drive technical decisions and participate in design reviews alongside senio

About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role AiDASH is looking for a high-agency Program Manager to help scale our AI Data Ops function: the team responsible for sourcing, processing, and annotating the satellite and remote sensing imagery that powers our AI/ML models. This role is a new addition to the leadership team, created specifically to bring an automation-first, numbers-backed, process-driven operating model to how Ops runs . This role is designed to reduce operational complexity over time, not to manage individual queues or projects indefinitely. You will sit at the intersection of strategy, operations, vendor management, and data science delivery, helping AI Data Ops evolve from a fast-scaling function into a well-designed, repeatable operating system. You will need to zoom in to solve real problems on the ground — a stuck vendor SLA, a high priority escalation, a broken handoff — and z

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

Roles and Responsibilities Building templates, dashboards in Excel /Google Sheet / PowerBI for operational and management reporting Statistical and Analytical Models and methods for data analysis related to customer initiatives & growth hacks including issue diagnosis, problem dissection and tracking of results Running and maintaining the reporting system Data extraction as per business request for Ad hoc analysis Assisting the team in data analysis and mining Business analysis and understanding to highlight key lead indicator Qualifications & Experience Bachelors in Engineering, Computer Science, Math, Statistics, or related discipline from a reputed institute or an MBA from a reputed institute 2+ years of experience in working on reporting / business intelligence systems Strong database concepts and experience in SQL – can convert any business requirement into a SQL statement Expertise in Excel, PowerBI Working experience in R, Python, Tableau, QlikView, Data studio is a good to have Experience of working in a customer growth/customer analytics role is a plus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines

AI Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI- powered innovations to enhance search relevance and ITSM workflows. What You Will Do: Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customerʼs data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 3-5 years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals who ask for payments in exchange for interviews or offer letter

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw