2099 Reinforcement Jobs - Page 49

Sprinklr is a leading enterprise software company for all customer-facing functions. With advanced AI, Sprinklr's unified customer experience management (Unified-CXM) platform helps companies deliver human experiences to every customer, every time, across any modern channel. Headquartered in New York City with employees around the world, Sprinklr works with more than 1,000 of the world’s most valuable enterprises — global brands like Microsoft, P&G, Samsung and more than 50% of the Fortune 100. Learn more about our culture and how we make our employees happier through The Sprinklr Way. Job Description What will you do: Work in a collaboration of machine learning engineers and data scientists. Work on various disciplines of machine learning including but not limited to variety of disciplines including deep learning, reinforcement learning, computer vision, language, speech processing etc. Work closely with machine learning leadership team to define and implement the technology and architectural strategy. Take partial ownership of project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-outs delivery. Deliver and maintain high-quality scalable systems in a timely and cost-effective manner. Recognising potential use-cases of cutting edge research in Sprinklr products and implementing your own solutions for the same. Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow. What makes you qualified: Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges. At least 2 years of Deep Learning Experience with a distinguished track record on technically fast paced projects. Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers. Experience with large language models (GPT-4, Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch). Working experience of software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations. Experience in communicating with users, other technical teams, and product management to understand requirements, describe software product features, and technical designs. Nice to have: Experience with Multi-Modal ML including Generative AI. Interested in and thoughtful about the impacts of AI technology. A real passion for AI! Why You'll Love Sprinklr: We're committed to creating a culture where you feel like you belong, are happier today than you were yesterday, and your contributions matter. At Sprinklr, we passionately, genuinely care. For full-time employees, we provide a range of comprehensive health plans, leading well-being programs, and financial protection for you and your family through a range of global and localized plans throughout the world. For more information on Sprinklr Benefits around the world, head to https://sprinklrbenefits.com/ to browse our country-specific benefits guides. We focus on our mission: We founded Sprinklr with one mission: to enable every organization on the planet to make their customers happier. Our vision is to be the world’s most loved enterprise software company, ever. We believe in our product: Sprinklr was built from the ground up to enable a brand’s digital transformation. Its platform provides every customer-facing team with the ability to reach, engage, and listen to customers around the world. At Sprinklr, we have many of the world's largest brands as our clients, and our employees have the opportunity to work closely alongside them. We invest in our people: At Sprinklr, we believe every human has the potential to be amazing. We empower each Sprinklrite in the journey toward achieving their personal and professional best. For wellbeing, this includes daily meditation breaks, virtual fitness, and access to Headspace. We have continuous learning opportunities available with LinkedIn Learning and more. EEO - Our philosophy: Our goal is to ensure every employee feels like they belong and are operating in a judgment-free zone regardless of gender, race, ethnicity, age, and lifestyle preference, among others. We value and celebrate diversity and fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we’re more innovative, creative, and successful. Sprinklr is proud to be an equal-opportunity workplace and is an affirmative-action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. See also Sprinklr’s EEO Policy and EEO is the Law.

We are hiring Structural CAD Draftsman position. Please find the details below. Position: Structural CAD Draftsman Experience: 4–7years Overview: We are looking for a skilled Structural CAD Draftsman with a strong background in preparing detailed structural drawings and documentation for building and infrastructure projects. The ideal candidate should have strong proficiency in AutoCAD and a solid understanding of international structural detailing standards and practices. Familiarity with Revit Structure and BIM workflows will be a significant advantage. If you're detail-oriented, technically sound, and passionate about structural drafting, we want to hear from you. Key Responsibilities: Prepare accurate and detailed structural drawings, including plans, elevations, sections, and connection details, with minimal supervision. Interpret and translate engineering markups, sketches, and specifications into CAD drawings. Produce GA drawings, reinforcement detailing, and schedules as per project requirements. Ensure all drawings are compliant with company and project standards, including applicable codes and client specifications. Maintain version control and proper organization of drawing files and documentation. Assist in the preparation of as-built drawings and revisions during construction phases. Ensure timely delivery of drawing packages in line with project schedules. Requirements: Bachelor’s degree or diploma in Civil Engineering. 4–6 years of proven experience in structural drafting, preferably in buildings and infrastructure projects. Proficiency in AutoCAD is essential; working knowledge of Revit Structure is a strong advantage. Solid understanding of structural systems including concrete, steel, wood, and masonry. Experience in preparing reinforcement detailing. Familiarity with international design standards such as ACI, BS, or Eurocodes. Strong attention to detail, accuracy, and quality assurance in drawings. Ability to work independently and collaboratively in a multidisciplinary environment. Good communication skills and the ability to meet tight deadlines across multiple projects. Job Type: Full-time Pay: ₹600,000.00 - ₹1,000,000.00 per year Schedule: Day shift Work Location: In person

About Us Green Rider Technology LLP is a fast-scaling engineering firm focused on post-training development and evaluation of large language models (LLMs). Our team of 250+ skilled engineers has contributed over 300,000 productive hours to advanced AI model pipelines, specializing in post-training workflows such as Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Evaluation. We work at the intersection of fullstack engineering and AI alignment, focusing on complex coding workflows, instruction-following validations, truthfulness assessments, and functional code verification across diverse tech stacks. Our strength lies in delivering technically sound and production-ready solutions with high operational efficiency. Location: Gurgaon (Work From Office) Employment Type: Full-Time Experience Required: 2–3 Years Open Roles: Software Engineers (Fullstack) Role Overview We are looking for experienced Fullstack Software Engineers who can contribute to post training AI development workflows with strong proficiency in coding tasks and evaluation logic. This role involves working on high-impact AI infrastructure projects, including but not limited to: Code generation, validation, and transformation across Python, Java, JavaScript, and modern frameworks Evaluation and improvement of model-generated code responses Designing and verifying web application features, APIs, and test cases used in AI model alignment Interpreting and executing task specifications to meet rigorous quality benchmarks Collaborating with internal teams to meet daily throughput and quality targets within a structured environment Key Responsibilities Work on fullstack engineering tasks aligned with LLM post-training workflows Analyze model-generated outputs for correctness, coherence, and adherence to task requirements Write, review, and verify application logic and coding prompts across supported language and frameworks Maintain consistency, quality, and efficiency in code-focused deliverables Engage with leads and PMs to meet productivity benchmarks (8–9 working hours daily) Stay updated with AI development standards and contribute to refining internal engineering processes Technical Skills Required Proficient in one or more backend languages: Python, Java, Node.js Strong experience in frontend technologies: React.js, HTML/CSS, TypeScript Familiarity with REST APIs, testing frameworks, and Git-based workflows Ability to analyze, debug, and rewrite logic for correctness and clarity Good understanding of model response evaluation and instruction-based coding logic Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 2–3 years of experience in a software development role (Fullstack preferred) Prior exposure to AI/LLM environments or code-based evaluation tasks is a plus Excellent written communication and logical reasoning abilities Comfortable working from office in Gurgaon and committing to 8–9 hours of productive work daily Why Join Us Be part of a high-growth team at the forefront of LLM post-training development Work on real-world AI engineering problems with production-grade impact Competitive compensation with performance-driven growth opportunities Structured workflow, collaborative culture, and technically challenging projects How to Apply Please share your resume at team-hr@greenridertech.com with the subject line: Application – Software Engineer (LLM Post-Training) Job Type: Permanent Pay: ₹70,000.00 - ₹80,000.00 per month Benefits: Leave encashment Paid sick time Paid time off Provident Fund Schedule: Day shift Monday to Friday Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Education: Bachelor's (Required) Experience: Fullstack Software Engineers: 2 years (Required) Location: Gurugram, Haryana (Preferred) Work Location: In person

S enior Fullstack AI/ML Engineer Location: Delhi Experience: 3-5 years Mode: On-site About the Role We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage. Responsibilities Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics. Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks. Fine-tune pre-trained models and develop custom models based on specific business needs. Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production. Collaborate with frontend/backend engineers to build AI-driven features into products or platforms. Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows. Ensure scalability and performance of deployed AI solutions within the full application stack. Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models. Design and implement APIs or services that expose machine learning models to frontend or other systems Internal Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions. Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems. Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions. Document processes, methodologies, and results for future reference and reproducibility. Required Skills & Qualifications Experience: 5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects. AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems. Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets. Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments. Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models. MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring. Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training. Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration. Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving. Understanding of system design and software architecture for integrating AI into production environments. Experience with frontend/backend integration (basic React/Next.js knowledge is a plus). Demonstrated projects where AI models were part of deployed user-facing applications. Internal NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects. Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage. Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions. Nice to Have Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques. Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes. Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.). Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes. Solid understanding of statistics and probability. Experience working in Agile development environments. What You'll Gain Be part of a forward-thinking team working on cutting-edge AI/ML technologies. Collaborate with a diverse, highly skilled team in a fast-paced environment. Opportunity to work on impactful projects with real-world applications. Competitive salary and career growth opportunities Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,200,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

About Magic Bus: Magic Bus India Foundation is a global non-profit organization that aims to empower and guide young people to break out of poverty and become productive members of their community. Magic Bus has been constantly awarded ‘Great Place To Work”, Founded in 1999 by Mr. Matthew Spacie. Magic Bus has impacted the lives of over 1 million young people across India through its Childhood to Livelihood program. Magic Bus operates 240 Community Learning Centres and is present in 2342 schools that work to enhance education, impart employability skills, and encourage entrepreneurship. For more information or to support our mission, visit our website at www.magicbus.org Job Title : Academic Educator Job Location: Keonjhar Overall Responsibility: Running a community learning centre to promote human development by providing opportunities for lifelong learning. To ensure that the children have a complete understanding of the foundational learning skills and develops their higher order thinking, leadership qualities, and makes children responsive to learning. To help adolescents to reach specific learning level which supports them to remain in school and complete their secondary schooling To enhance the adolescent quality of life. Roles and responsibilities: To identify and provide study support to children who would need remedial support along with providing them an opportunity for learning by doing. To be able to give community information and resource services and to engage in community development activities, co-ordination and networking. To be able to improve academic skills and address the key reason of drop outs and learning gaps. To focus on developing basic literacy, foundational numeracy skills (Grades 6-8), access to learning & improved learning outcome (Grade 6 to 9), focus on learning Enhancement & class 10 completion (Exam Preparation) (Grade 9 & 10) grade specific language and mathematics in students and facilitate them in the process of learning before and after school. To create a congenial learning environment which encourages collaborative joyful learning among children to increase their interest in learning as well as provide grade appropriate inputs for subjects like language, science and mathematics to improve learning. To be able to work on learning reinforcement and practice including periodical evaluation with the children. To manage the centre and work with learners from grade 6 to 10 with a maximum of 35 students per session. Effective delivery of Program Module with adolescents studying in grade 6th- 10th in the community learning centre. To engage children studying in grades 6th to 10th with various creative teaching learning and peer learning strategies at school and community level effectively deliver various activities for reading, communication, science, art and craft. To prepare yearly, monthly weekly plans, along with daily lesson plans and worksheets and to enable children to carry out subject activities as well as ensure timely completion of desired learning objectives. To engage children in competitions ,educational games (like scrabble, puzzles) and art and craft activities to promote joyful learning as well as involve parents and locale from community to captivate children in their area of expertise. To arrange learning activities involving digital learning platforms, basic fundamentals of computers and coding with help of self-learning make a different material. To engage with parents quarterly and update them on the progress of their child’s progress. To work with life skills educator (LSE) in co-ordination and provide support to the Community Co-ordinators in various community engagement activities like parents meeting (Parents, workshop) for the adolescent in the community. To participate in the capacity building programs as per the project design and to provide constant feedback/ learning’s on the basis of implemented curriculum. To support and facilitate data collection for M&E purposes and maintain records like MIS, attendance and daily activities conducted by children. To keep oneself updated on all the developments in safety rules, regulation child rights and protection and ensuring its integration in programs. To ensure effective communication and reporting upward and down the line of all matters related to the efficiency and effectiveness of the program and to provide timely documented quality updates and reports to key stakeholders regularly. To do capacity building of community coordinators from time to time. To facilitate/organize/participate in events, visits as required. Academic Educator and Life Skill Educator will work in co-ordination. Job Type: Full-time Pay: ₹18,000.00 - ₹21,000.00 per month Benefits: Cell phone reimbursement Health insurance Provident Fund Schedule: Day shift Education: Bachelor's (Required) Experience: teaching: 1 year (Preferred) Work Location: In person

Software Engineer, Infrastructure & DevOps Train large-language models (LLMs) to write production-grade infrastructure and DevOps code Help teach AI how to write, debug, and optimize infrastructure code like a top-tier DevOps engineer. Compare and rank Terraform or IaC code snippets, explaining which is more reliable, efficient, or scalable. Refactor or repair AI-generated infrastructure setups for correctness, security, and clarity. Provide structured feedback (edits, test outcomes, architectural notes) that feeds into the RLHF pipeline. End result: The model learns to reason about DevOps the way you do—smart, scalable, and safe. RLHF in one line Generate IaC or backend code ➜ expert engineers rank, edit, and explain ➜ convert feedback into reward signals ➜ reinforcement learning tunes the model to think like a real infra engineer. What Is Needed 4+ years of professional software-engineering experience , ideally in backend, infrastructure, or DevOps. Extreme attention to detail and excellent written communication —you’ll be writing a lot of thoughtful code reviews and architectural justifications. Fluency with cloud infrastructure , especially AWS . Hands-on experience with Terraform and Infrastructure as Code practices. Strong instincts for performance, cost optimization, and security . Comfortable in a low-oversight, async-first remote environment . You enjoy reading documentation and specs—seriously. What Is Not Needed No prior RLHF or AI-training experience required. No machine learning expertise needed—just deep infra/DevOps experience and clear thinking. Tech Stack We are especially looking for backend engineers working in Infra or Terraform-heavy environments. Experience with any of the following is highly valued: Terraform, AWS, GCP, or other cloud providers Node.js or backend scripting CI/CD pipelines Infrastructure as Code (IaC) best practices Logistics Location: Fully remote (work from anywhere) Hours: Minimum 15 hrs/week, can go up to 40 hrs/week Engagement: 1099 contract

Job Title: Business Development Executive (BDE) Company: Ruby Build Care LLP Location: Ahmedabad (with travel to other regions as required) Industry: Construction Chemicals (Waterproofing, Reinforcement, Tile & Stone Adhesives) Employment Type: Full-time Experience Required: 0–5 years in B2B Sales / Construction Chemical Industry preferred About the Company: Ruby Build Care LLP is a fast-growing manufacturer of premium construction chemicals, with a strong focus on waterproofing solutions , reinforcement products , and tile & stone adhesives . We serve both retail and project-based clients, delivering innovative, reliable, and long-lasting solutions for modern construction needs. Key Responsibilities: Lead Generation & Business Expansion: Identify and approach potential clients: builders, contractors, waterproofing agencies, architects, and applicators. Develop relationships with dealers/distributors to expand market reach. Drive business growth in Ahmedabad and other assigned territories. Sales & Target Achievement: Achieve monthly and quarterly sales targets across product categories. Maintain and expand client database within your assigned territory. Client Relationship Management: Act as a point of contact for customer inquiries, product demos, and technical support (with the help of the technical team). Maintain long-term relationships with key clients and stakeholders. Project Coordination: Track ongoing projects and follow up for product approvals and order closures. Coordinate with internal teams for timely delivery, payment follow-up, and client satisfaction. Market Intelligence & Reporting: Monitor competitor activities, pricing strategies, and market trends. Prepare daily/weekly reports for management review. Training & Product Awareness: Organize product demos, technical sessions, and on-site trials for customers. Attend company training programs to stay updated with product innovations. Qualifications: Graduate/Diploma in Civil Engineering, BBA/MBA in Marketing, or relevant field. Proven field sales experience in construction chemicals or building materials preferred. Strong communication, negotiation, and presentation skills. Self-motivated with a results-driven approach. Willingness to travel within and outside Ahmedabad. Compensation & Incentives: Base Salary: Competitive and based on experience. Performance Incentives: Attractive target-based incentives. Allowances: Travel and mobile allowances as per company policy. Growth Opportunities: Fast-track career growth based on performance. Job Types: Full-time, Permanent, Fresher Pay: ₹15,000.00 - ₹25,000.00 per month Schedule: Day shift Supplemental Pay: Commission pay Performance bonus Quarterly bonus Yearly bonus Language: Hindi, Gujarati, English (Preferred) Work Location: In person Expected Start Date: 20/06/2025

Job Title: Telecalling Recruiter – Blue Collar Hiring Location: 38, Paddana Reddy Layout Rd, Nanjappa Garden, Horamavu, Bengaluru, Karnataka 560043 Company: G4S Secure Solutions (India) Pvt. Ltd. Reporting To: Regional Recruitment Lead – South Zone Compensation: As per company standards + Incentives (based on performance) Working Days & Hours: Monday to Saturday | 9:00 AM to 6:00 PM Role Purpose We are seeking a proactive and target-oriented Telecalling Recruiter to support high-volume blue-collar hiring for our security guarding operations across Karnataka. This role requires someone who is comfortable working on the phone, engaging with candidates from semi-urban and rural areas, and ensuring a steady pipeline of eligible candidates for training and deployment. Key Responsibilities Telecalling & Candidate Sourcing Make outbound calls to job seekers, job portals, referral networks, and past candidate databases. Clearly communicate job role, salary, documents required, and benefits to prospective candidates. Maintain a daily call count and engagement tracker. Candidate Screening & Follow-up Perform initial candidate screening over the phone – age, physical fitness, documents, location preferences, etc. Convince eligible candidates to report to the nearest training center or recruitment hub. Schedule and follow up with candidates for documentation and joining formalities. Database Management Maintain accurate candidate records in Excel or internal software – contact info, status, follow-up dates, etc. Ensure database is clean, duplicate-free, and updated daily with correct status (Interested Not Interested Joined Rejected). Outreach & Campaigns Support WhatsApp broadcast, SMS campaigns, and local outreach activities as per guidance. Coordinate with the field sourcing team for village visits, camps, or referral schemes. Candidate Profile Essential Qualifications & Skills Minimum: 10+2 or Graduate in any discipline Good communication skills in Kannada, Hindi, and basic English Confident and polite phone manner with ability to influence rural candidates Basic computer knowledge: MS Excel, WhatsApp, email, and web browsing Prior experience in a call center, tele-sales, or recruitment is preferred Preferred Background Recruitment for manpower agencies, staffing firms, or facilitysecurity services Familiarity with Kannada-speaking regions and rural demographics Performance Expectations Minimum daily outbound calls: 100–150 Weekly joining targets: 20+ candidates (for training) Regular tracking of follow-ups and database hygiene Incentives based on achieving weeklymonthly joining targets Why Join G4S Secure Solutions? Be part of a global leader in security and manpower solutions Fixed working hours and salary with performance-based incentives Career growth opportunities into field recruitment, team handling, or HR operations Supportive and structured recruitment process with tools, templates, and leads provided Contact Person for This Vacancy: Name: Abhay Mulik Mobile: +91 9972877452 WhatsApp: +91 9113627282 Email: abhay.mulik@in.g4s.com

Job Title: Senior Python Developer – Trading Systems & Market Data Experience: 3–4 Years Location: Hyderabad, Telangana (On-site) Employment Type: Full-Time About the Role: We are seeking a Senior Python Developer with 3–4 years of experience and a strong understanding of stock market dynamics, technical indicators, and trading systems. You’ll take ownership of backtesting frameworks, strategy optimization, and developing high-performance, production-ready trading modules. The ideal candidate is someone who can think critically about trading logic, handle edge cases with precision, and write clean, scalable, and testable code. You should be comfortable working in a fast-paced, data-intensive environment where accuracy and speed are key. Key Responsibilities: Design and maintain robust backtesting and live trading frameworks. Build modules for strategy development, simulation, and optimization. Integrate with real-time and historical market data sources (e.g., APIs, databases). Use libraries like Pandas, NumPy, TA-Lib, Matplotlib, SciPy, etc., for data processing and signal generation. Apply statistical methods to validate strategies (mean, regression, correlation, standard deviation, etc.). Optimize code for low-latency execution and memory efficiency. Collaborate with traders and quants to implement and iterate on ideas. Use Git and manage codebases with best practices (unit testing, modular design, etc.). Required Skills & Qualifications: 3–4 years of Python development experience, especially in data-intensive environments. Strong understanding of algorithms, data structures, and performance optimization. Hands-on with technical indicators, trading strategy design, and data visualization. Proficient with Pandas, NumPy, Matplotlib, SciPy, TA-Lib, etc. Strong SQL skills and experience working with structured and time-series data. Exposure to REST APIs, data ingestion pipelines, and message queues (e.g., Kafka, RabbitMQ) is a plus. Experience in version control systems (Git) and collaborative development workflows. Preferred Experience: Hands-on experience with trading platforms or algorithmic trading systems. Familiarity with order management systems (OMS), execution logic, or market microstructure. Prior work with cloud infrastructure (AWS, GCP) or Docker/Kubernetes. Knowledge of machine learning or reinforcement learning in financial contexts is a bonus. What You’ll Get: Opportunity to work on real-world trading systems with measurable impact. A collaborative and fast-paced environment. A role where your ideas directly translate to production and trading performance. Job Type: Full-time Pay: ₹400,000.00 - ₹900,000.00 per year Location Type: In-person Schedule: Day shift Work Location: In person

Sprinklr is a leading enterprise software company for all customer-facing functions. With advanced AI, Sprinklr's unified customer experience management (Unified-CXM) platform helps companies deliver human experiences to every customer, every time, across any modern channel. Headquartered in New York City with employees around the world, Sprinklr works with more than 1,000 of the world’s most valuable enterprises — global brands like Microsoft, P&G, Samsung and more than 50% of the Fortune 100. Learn more about our culture and how we make our employees happier through The Sprinklr Way. Job Description What will you do: Work in a collaboration of machine learning engineers and data scientists. Work on various disciplines of machine learning including but not limited to variety of disciplines including deep learning, reinforcement learning, computer vision, language, speech processing etc. Work closely with machine learning leadership team to define and implement the technology and architectural strategy. Take partial ownership of project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-outs delivery. Deliver and maintain high-quality scalable systems in a timely and cost-effective manner. Recognising potential use-cases of cutting edge research in Sprinklr products and implementing your own solutions for the same. Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow. What makes you qualified: Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges. At least 2 years of Deep Learning Experience with a distinguished track record on technically fast paced projects. Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers. Experience with large language models (GPT-4, Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch). Working experience of software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations. Experience in communicating with users, other technical teams, and product management to understand requirements, describe software product features, and technical designs. Nice to have: Experience with Multi-Modal ML including Generative AI. Interested in and thoughtful about the impacts of AI technology. A real passion for AI! Why You'll Love Sprinklr: We're committed to creating a culture where you feel like you belong, are happier today than you were yesterday, and your contributions matter. At Sprinklr, we passionately, genuinely care. For full-time employees, we provide a range of comprehensive health plans, leading well-being programs, and financial protection for you and your family through a range of global and localized plans throughout the world. For more information on Sprinklr Benefits around the world, head to https://sprinklrbenefits.com/ to browse our country-specific benefits guides. We focus on our mission: We founded Sprinklr with one mission: to enable every organization on the planet to make their customers happier. Our vision is to be the world’s most loved enterprise software company, ever. We believe in our product: Sprinklr was built from the ground up to enable a brand’s digital transformation. Its platform provides every customer-facing team with the ability to reach, engage, and listen to customers around the world. At Sprinklr, we have many of the world's largest brands as our clients, and our employees have the opportunity to work closely alongside them. We invest in our people: At Sprinklr, we believe every human has the potential to be amazing. We empower each Sprinklrite in the journey toward achieving their personal and professional best. For wellbeing, this includes daily meditation breaks, virtual fitness, and access to Headspace. We have continuous learning opportunities available with LinkedIn Learning and more. EEO - Our philosophy: Our goal is to ensure every employee feels like they belong and are operating in a judgment-free zone regardless of gender, race, ethnicity, age, and lifestyle preference, among others. We value and celebrate diversity and fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we’re more innovative, creative, and successful. Sprinklr is proud to be an equal-opportunity workplace and is an affirmative-action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. See also Sprinklr’s EEO Policy and EEO is the Law.

S enior Fullstack AI/ML Engineer Location: Delhi Experience: 3-5 years Mode: On-site About the Role We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage. Responsibilities Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics. Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks. Fine-tune pre-trained models and develop custom models based on specific business needs. Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production. Collaborate with frontend/backend engineers to build AI-driven features into products or platforms. Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows. Ensure scalability and performance of deployed AI solutions within the full application stack. Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models. Design and implement APIs or services that expose machine learning models to frontend or other systems Internal Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions. Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems. Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions. Document processes, methodologies, and results for future reference and reproducibility. Required Skills & Qualifications Experience: 5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects. AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems. Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets. Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments. Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models. MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring. Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training. Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration. Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving. Understanding of system design and software architecture for integrating AI into production environments. Experience with frontend/backend integration (basic React/Next.js knowledge is a plus). Demonstrated projects where AI models were part of deployed user-facing applications. Internal NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects. Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage. Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions. Nice to Have Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques. Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes. Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.). Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes. Solid understanding of statistics and probability. Experience working in Agile development environments. What You'll Gain Be part of a forward-thinking team working on cutting-edge AI/ML technologies. Collaborate with a diverse, highly skilled team in a fast-paced environment. Opportunity to work on impactful projects with real-world applications. Competitive salary and career growth opportunities Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,200,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

Job Summary: Act as domain experts in facilitating the fine-tuning of AI models, via techniques like Prompt Engineering and Reinforcement Learning Review/Generate technical content Help train state-of-the-art Large Language Models (LLMs) ​Required Qualifications: Graduation in any field; further education or certifications in transcription is a plus. Proven experience as a transcriber/annotator or in a similar role is an added advantage. Excellent listening skills and attention to detail. Strong command of English grammar, punctuation, and spelling. Proficiency in typing with a high level of accuracy. Must know basic computer skills. Ability to work independently and manage time effectively. Should be able to understand various accents. Working model: Monda y - Saturday 9am- 6pm Benefits: Opportunity to work on cutting-edge technology projects. Collaborative and inclusive work environment. Career growth and professional development opportunities. A culture that values innovation and creativity.

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that’s critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future. Department Overview The Design & Tools (D&T) team is a strategic component of Centralized Managed Support Operations (CMSO), responsible for providing exceptional Service Design & innovative technology solutions to enable and empower MSI Centralized Managed Support Operations to meet and exceed customer's expectations. In this role, you will fit in the AI & Architecture team within D&T. Job Description We are looking for a Senior Data Scientist who will also serve as a subject matter expert in the AI and ML domain, and build analytical and statistical machine learning models that will drive business decisions. In this role You will understand user requirements and translate them into AI solutions that turbocharge internal and external user experiences. Many of these AI solutions will be enabled within the core technologies used within CMSO, including Salesforce and ServiceNow. In other instances, you will also be responsible for building custom predictive and prescriptive ML models for preventative system health checks, system log analytics, automated root cause analysis etc. Responsibilities include: Drive requirements for AI related projects, work with internal customers and with ServiceNow and Salesforce Product Managers for features planning, prioritization and implementation Understand and apply various statistical methods for data analysis, EDA, hypothesis testing, and drawing meaningful conclusions. Apply GenAI, ML and DL concepts, NLP, computer vision, sentiment analysis, topic modeling and graph theory in real world applications to solve business problems Develop application-specific interfaces that leverage GenAI capabilities and LLMs to enhance the associate and customer experience. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Leverage Python, PyTorch, NLTK etc. libraries and frameworks such as Langchain to build AI solutions. Training ML models to effectively communicate complex data insights through clear and informative visualizations Serves as thought leader in data science and applies deep expertise to drive novel customer experiences Adaptive and the desire to learn new technologies. Technical Experience Extensive knowledge of AI supervised, unsupervised and reinforcement methods, GenAI LLM and Python libraries to perform data analysis, building advanced machine learning models and data integrations with source systems and systems of record Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, or spaCy Very good knowledge and experience with Databases like Postgres, Redshift, MSSQL Knowledge and experience in Cloud Environments (Azure, AWS, GCP) Experience to read data from multiple sources and cleanse, enhance and analyze the data. Ability to integrate data, sourcing data from several Sources including databases, files, API and Server logs. Preferred Qualifications Minimum of 4+ years experience in data analytics, data mining, machine learning, and has employed predictive, prescriptive, conversational or generative AI to solve business problems Minimum of 4+ years experience in hands-on design, coding, development and deployment using data science tools such as Python, Tensorflow etc. to build AI solutions Minimum 2+ years experience leading teams to deliver solutions and results Deep knowledge of ML streams, e.g., natural language processing, computer vision, statistical learning theory and their application in real world situations Knowledge of ServiceNow and Salesforce products and features Experience working with one of the leading public clouds (AWS, Google, Azure) Excellent written and oral communication skills. Be able to work under pressure Ability to Multitask, Prioritize and Manage time effectively. Strong interpersonal skills and ability to work effectively across teams, functional groups Basic Requirements Bachelor's degree in Data Science, Computer Science, or an IT related field Minimum of 4+ years experience in a Data Science related role Travel Requirements None Relocation Provided None Position Type Experienced Referral Payment Plan No EEO Statement Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic. We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

About Us Green Rider Technology LLP is a fast-scaling engineering firm focused on post-training development and evaluation of large language models (LLMs). Our team of 250+ skilled engineers has contributed over 300,000 productive hours to advanced AI model pipelines, specializing in post-training workflows such as Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Evaluation. We work at the intersection of fullstack engineering and AI alignment, focusing on complex coding workflows, instruction-following validations, truthfulness assessments, and functional code verification across diverse tech stacks. Our strength lies in delivering technically sound and production-ready solutions with high operational efficiency. Location: Gurgaon (Work From Office) Employment Type: Full-Time Experience Required: 2–3 Years Open Roles: Software Engineers (Fullstack) Role Overview We are looking for experienced Fullstack Software Engineers who can contribute to post training AI development workflows with strong proficiency in coding tasks and evaluation logic. This role involves working on high-impact AI infrastructure projects, including but not limited to: Code generation, validation, and transformation across Python, Java, JavaScript, and modern frameworks Evaluation and improvement of model-generated code responses Designing and verifying web application features, APIs, and test cases used in AI model alignment Interpreting and executing task specifications to meet rigorous quality benchmarks Collaborating with internal teams to meet daily throughput and quality targets within a structured environment Key Responsibilities Work on fullstack engineering tasks aligned with LLM post-training workflows Analyze model-generated outputs for correctness, coherence, and adherence to task requirements Write, review, and verify application logic and coding prompts across supported language and frameworks Maintain consistency, quality, and efficiency in code-focused deliverables Engage with leads and PMs to meet productivity benchmarks (8–9 working hours daily) Stay updated with AI development standards and contribute to refining internal engineering processes Technical Skills Required Proficient in one or more backend languages: Python, Java, Node.js Strong experience in frontend technologies: React.js, HTML/CSS, TypeScript Familiarity with REST APIs, testing frameworks, and Git-based workflows Ability to analyze, debug, and rewrite logic for correctness and clarity Good understanding of model response evaluation and instruction-based coding logic Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 2–3 years of experience in a software development role (Fullstack preferred) Prior exposure to AI/LLM environments or code-based evaluation tasks is a plus Excellent written communication and logical reasoning abilities Comfortable working from office in Gurgaon and committing to 8–9 hours of productive work daily Why Join Us Be part of a high-growth team at the forefront of LLM post-training development Work on real-world AI engineering problems with production-grade impact Competitive compensation with performance-driven growth opportunities Structured workflow, collaborative culture, and technically challenging projects How to Apply Please share your resume at team-hr@greenridertech.com with the subject line: Application – Software Engineer (LLM Post-Training) Job Type: Permanent Pay: ₹70,000.00 - ₹80,000.00 per month Benefits: Leave encashment Paid sick time Paid time off Provident Fund Schedule: Day shift Monday to Friday Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Education: Bachelor's (Required) Experience: Fullstack Software Engineers: 2 years (Required) Location: Gurugram, Haryana (Preferred) Work Location: In person

Title : Lead Data Scientist/ML Engineer (5+ years & above) Required Technical Skillset : (GenAI) Language : Python Framework : Scikit-learn, TensorFlow, Keras, PyTorch, Libraries : NumPy, Pandas, Matplotlib, SciPy, Scikit-learn - DataFrame, Numpy, boto3 Database : Relational Database(Postgres), NoSQL Database (MongoDB) Cloud : AWS cloud platforms Other Tools : Jenkins, Bitbucket, JIRA, Confluence A machine learning engineer is responsible for designing, implementing, and maintaining machine learning systems and algorithms that allow computers to learn from and make predictions or decisions based on data. The role typically involves working with data scientists and software engineers to build and deploy machine learning models in a variety of applications such as natural language processing, computer vision, and recommendation systems. The key responsibilities of a machine learning engineer includes : Collecting and preprocessing large volumes of data, cleaning it up, and transforming it into a format that can be used by machine learning models. Model building which includes Designing and building machine learning models and algorithms using techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning. Evaluating the model performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score. Deploying machine learning models in production environments and integrating them into existing systems using CI/CD Pipelines, AWS Sagemaker Monitoring the performance of machine learning models and making adjustments as needed to improve their accuracy and efficiency. Working closely with software engineers, product managers and other stakeholders to ensure that machine learning models meet business requirements and deliver value to the organization. Requirements And Skills Mathematics and Statistics : A strong foundation in mathematics and statistics is essential. They need to be familiar with linear algebra, calculus, probability, and statistics to understand the underlying principles of machine learning algorithms. Programming Skills Should be proficient in programming languages such as Python. The candidate should be able to write efficient, scalable, and maintainable code to develop machine learning models and algorithms. Machine Learning Techniques Should have a deep understanding of various machine learning techniques, such as supervised learning, unsupervised learning, and reinforcement learning and should also be familiar with different types of models such as decision trees, random forests, neural networks, and deep learning. Data Analysis And Visualization Should be able to analyze and manipulate large data sets. The candidate should be familiar with data cleaning, transformation, and visualization techniques to identify patterns and insights in the data. Deep Learning Frameworks Should be familiar with deep learning frameworks such as TensorFlow, PyTorch, and Keras and should be able to build and train deep neural networks for various applications. Big Data Technologies A machine learning engineer should have experience working with big data technologies such as Hadoop, Spark, and NoSQL databases. They should be familiar with distributed computing and parallel processing to handle large data sets. Software Engineering A machine learning engineer should have a good understanding of software engineering principles such as version control, testing, and debugging. They should be able to work with software development tools such as Git, Jenkins, and Docker. Communication And Collaboration A machine learning engineer should have good communication and collaboration skills to work effectively with cross-functional teams such as data scientists, software developers, and business stakeholders. (ref:hirist.tech)

Job Description AI Lead - Innovation & Product Development About Us KPMG is a dynamic and forward-thinking Professional service firm committed to leveraging cutting-edge artificial intelligence to create transformative products and solutions. We are building a team of passionate innovators who thrive on solving complex challenges and pushing the boundaries of what's possible with AI. Job Summary We are seeking an experienced and visionary AI Lead to spearhead our AI innovation and product development. The ideal candidate will be a hands-on leader with a strong background in solution architecture, a proven track record in developing AI-based products, and deep expertise in Generative AI applications, including Agentic AI. This role requires a comprehensive understanding of AI models, frameworks, and Agentic AI, along with exposure to GPU infrastructure, to design, build, and deploy scalable AI solutions. You will drive our AI strategy, lead cross-functional teams, and transform complex ideas into tangible, market-ready products, with a strong understanding of enterprise requirements from a professional services perspective. Key Responsibilities Strategic Leadership & Innovation: Define and drive the AI innovation roadmap, identifying emerging trends in AI, Generative AI and Agentic AI. Lead research, evaluation, and adoption of new AI models, algorithms, and frameworks. Foster a culture of continuous learning, experimentation, and innovation. AI Product Development & Management: Lead end-to-end development of AI-based products, from ideation to deployment and optimization. Collaborate with product managers, designers, and stakeholders to translate business requirements into viable AI solutions. Ensure successful delivery of high-quality, scalable, and performant AI products. Client Engagement & Solutioning: Work with multiple clients to understand requirements, design tailored AI solutions, develop proofs-of-concept (POCs), and ensure successful implementation in a professional services context. Solution Architecture & Design: Design robust, scalable, and secure AI solution architectures across multi-cloud platforms and on-premise infrastructure. Provide technical guidance and architectural oversight for AI initiatives, focusing on optimizing for GPU infrastructure . Evaluate and recommend AI technologies, tools, and infrastructure, including Large Language Models (LLMs) and Small Language Models (SLMs) on cloud and on-premise. Team Leadership & Mentorship: Lead, mentor, and grow a team of talented AI engineers, data scientists, and machine learning specialists. Conduct code reviews and ensure adherence to coding standards and architectural principles. Promote collaboration and knowledge sharing. Technical Expertise & Implementation: Hands-on experience in developing and deploying Generative AI applications (e.g., LLMs, RAG, GraphRags , image generation, code generation), including Agentic AI and Model Context Protocol (MCP). Proficiency with Agentic AI orchestration frameworks such as LangChain, LlamaIndex, and/or similar tools. Experience with leading LLM providers and models including OpenAI, Llama, Anthropic, and others. Familiarity with AI-powered tools and platforms such as Microsoft Copilot, GitHub Copilot etc. Strong understanding of various machine learning models (deep learning, supervised, unsupervised, reinforcement learning). Experience with large datasets, ensuring data quality, feature engineering, and efficient data processing for AI model training. Deep understanding of GPU infrastructure, for AI model training or/ and inference. Qualifications Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or a related quantitative field. 8+ years in AI/ML development, with at least 3 years in a leadership or lead architect role. Mandatory: Proven experience in leading the development and deployment of AI-based products and solutions. Mandatory: Extensive hands-on experience with Generative AI models and frameworks (e.g., TensorFlow, PyTorch, Hugging Face, OpenAI APIs, etc.), including practical application of Agentic AI. Proficiency with Agentic AI orchestration frameworks such as LangChain, LlamaIndex, and/or similar tools. Experience in leveraging and integrating various LLM providers and models, including but not limited to OpenAI, Llama, and Anthropic. Familiarity with AI-powered development tools and platforms such as Microsoft Copilot, GitHub Copilot, and other code generation/assistance tools. Strong understanding of solution architecture principles for large-scale AI systems, including multi-cloud platforms and on-premise deployments. Mandatory: Exposure to and understanding of GPU infrastructure, especially NVIDIA, for AI workloads. Experience with Large Language Models (LLMs) and Small Language Models (SLMs) on both cloud and on-premise environments. Proficiency in programming languages such as Python, with strong software engineering fundamentals. Familiarity with MLOps practices, including model versioning, deployment, monitoring, and retraining. Mandatory: Demonstrated industry exposure to professional services, with a proven track record of working with multiple clients to solution requirements, conduct POCs, and understand enterprise-level needs. Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to diverse audiences. Strong problem-solving abilities and a strategic mindset. What We Offer Opportunity to work on cutting-edge AI technologies and shape the future of our products. A collaborative and innovative work environment. Competitive salary and benefits package. Professional development and growth opportunities. The chance to make a significant impact on our business and our customers. If you are a passionate AI leader with a drive for innovation and a desire to build groundbreaking AI products, we encourage you to apply!

Introduction IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing, always choosing the big, urgent and mind-bending work that endures and shapes generations. Our passion for discovery, and excitement for defining the future of tech, is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make. IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive. Your Role And Responsibilities Research Scientist position at IBM India Research Lab is a challenging, dynamic and highly innovative role, where you will be responsible for coming up with new innovative ideas, developing solutions working as a team, building prototypes, publishing research papers and demonstrating the value of your ideas in an enterprise setting. Some of our current areas of work where we are actively looking for top researchers are: Optimized runtime stacks for foundation model workloads including fine-tuning, inference serving and large-scale data engineering, with a focus on multi-stage tuning including reinforcement learning, inference-time compute, and data preparation needs for complex AI systems. Optimizing models to run on multiple accelerators including IBM’s AIU accelerator leveraging compiler optimizations, specialized kernels, libraries and tools. Innovative use cases that effectively leverage the infrastructure and models to deliver value Pre-training language and multi-modal foundation models working with large scale distributed training procedures, model alignment, and creating specialized pipelines for various tasks including effective LLM-generated data pipelines. Required Technical And Professional Expertise You should have one or more of the following: A master’s degree in computer science, AI or related fields from a top institution 0-8 years of experience working with modern ML techniques including but not limited to model architectures, data processing, fine-tuning techniques, reinforcement learning, distributed training, inference optimizations Experience with big data platforms like Ray and Spark Experience working with Pytorch FSDP and HuggingFace libraries Programming experience in one of the following: Python, web development technologies Growth mindset and a pragmatic attitude Preferred Technical And Professional Experience Peer-reviewed research at top machine learning or systems conferences Experience working with pytorch.compile, CUDA, triton kernels, GPU scheduling, memory management Experience working with open-source communities

Sprinklr was founded in 2009 to solve a big problem: enterprise-size complexity dividing brands from the customers they serve. The idea was to unify silos, technology, and teams across large, complex companies. What started in social expanded into a single AI platform to reach, engage, and listen to customers on more than 30 digital channels. Today, Sprinklr has an AI-based platform for four product suites: Sprinklr Service, Sprinklr Social, Sprinklr Marketing and Sprinklr Insights. And as customer-facing teams, markets, and geographies work together, brands benefit from a unified digital edge. At Sprinklr, the culture is built around pushing the limits of possibility. Social media today has changed the world, with each of us playing a role in the future. The Company strives to delight customers by going above and beyond as a trusted social guide and helping reimagine enterprise software for the better, with a core belief in the Sprinklr Way. Job Title: Director of Machine Learning Research Location: Gurugram Responsibilities: Set Research Direction: Define and execute a forward-looking ML research agenda aligned with company strategy and business objectives and technological innovation. Drive Key Research in relevant areas of Sprinklr: Self-learning AI Agents, Auto Evaluation of AI Agents, Taxonomy discovery and quality, End-to-end voice models, Multi-linguality, Multi-modality, Domain-Specific finetuning and alignment, etc. Advance the State of the Art: Guide research initiatives in areas such as deep learning, generative models, NLP, and reinforcement learning. Encourage and support filing patents and publications in top-tier venues (NeurIPS, ICML, ACL, CVPR, IEEE etc.). Bridge Research and Product: Collaborate with engineering and product teams to transition research into real-world applications. Champion best practices in experimentation, reproducibility, and scalability. Lead and Grow the Team: Mentor and manage a high-performing team of ML researchers and engineers. Foster a culture of curiosity, rigor, and excellence. Act as a Thought Leader: Stay ahead of emerging trends and shape the company's position in the global AI landscape. Evangelism : Serve as a subject matter expert internally and externally. Represent the company in academic and industry events, talks, and panels. Qualifications: Deep expertise in modern ML techniques, especially large-scale learning, generative models, or foundational models. Experienced with synthetic dataset generation for production and quantization. PhD in Computer Science, Machine Learning, or a related field. 8+ years of experience in ML/AI, including 4+ years in a leadership role. Proven track record of impactful research contributions, including publications, patents, or open-source work. Strong knowledge of cloud platform technologies and MLops tools such as CUDA, K8s, Docker, PyTorch, TensorRT, etc. Strong leadership and communication skills, with experience managing senior researchers and cross-functional collaboration. Ability to align research investments with business strategy and measurable outcomes.

Relocation Assistance Offered Within Country Job Number #167664 - Mumbai, Maharashtra, India Who We Are Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name! Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all. Title: Assistant Manager, Global Data Science Brief introduction - Role Summary/Purpose: The Global Data Science team at Colgate-Palmolive builds and deploys analytics solutions to drive business growth, focusing on areas like Price Elasticity, Trade Promo Efficiency, and Marketing Effectiveness. To meet increasing demand, new geographically based "Advanced Analytics Pods" are being created, with this role leading the "Europe and Africa Eurasia Pod" and managing six data scientists. This position involves close collaboration with the capability center, Division Analytics and business teams to understand needs, prioritize projects, and deliver relevant analytics solutions. The role requires strong expertise in statistical data analytics, machine learning/AI, and CPG analytics to develop predictive models, manage large datasets, and translate insights into business impact. Responsibilities: Leads the scoping and delivery of Pricing, Promotion, and Marketing Effectiveness analytics, including conceptualizing and building predictive models, machine learning algorithms, and optimization solutions. Plays a key role in the governance and continuous improvement of internal analytics solutions, collaborating with other Advanced Analytics Pods. Translates complex analytical results and insights into easily understandable and actionable recommendations for business teams, effectively bridging the gap between business needs and data science. Develops and manages visualization deliverables and web applications to enable self-service analytics and diagnostics for various functions. Writes SQL and Python code to build and deploy scalable enterprise-level data science solutions (e.g., Marketing Mix Modeling, Revenue Growth Management) on cloud platforms using tools like Airflow, Docker, and Kubernetes. Leads, mentors, and coaches a team of data scientists, ensuring the quality of recommendations and solutions deployed globally, and drives new value by integrating internal and external data. Collaborates effectively with cross-functional teams (GIT, Data Architecture, Analytics Engineering) and business partners across geographies and time zones, assisting with change management and presenting insights to stakeholders. Required Qualifications: Educational Background & Experience: Requires a Bachelor's degree (Master's/MBA preferred) in a quantitative/technical field (Data Science, Engineering, Statistics, Economics, etc.) with 7+ years in data science and analytics, including 2+ years managing/setting up a data science team. Advanced Technical Expertise: Strong hands-on experience developing and deploying statistical models and machine learning algorithms (Regression, Random Forest, XGBOOST, Clustering, etc.) in production, with expert coding skills in Python, SQL, PySpark, and R. MLOps & Cloud Proficiency: Demonstrable experience with MLOps practices (GitHub, Airflow, Docker, Kubernetes, Databricks, Dataiku) and cloud platforms like Google Cloud and Snowflake, managing high-volume, varied data sources. Domain Specialization & Business Acumen: Expert knowledge in Marketing Mix Modeling, Revenue Growth Management, Optimization, Forecasting, and Marketing Analytics, preferably in CPG or consulting, with the ability to think strategically in complex business contexts. Client-Facing & Communication Skills: Proven experience in a client-facing role, supporting multi-functional teams, with exceptional communication, collaboration, presentation, and storytelling skills to convey insights to business stakeholders. Project Leadership & Execution: Ability to independently plan and execute deliveries, lead project teams for predictive modeling and ad-hoc data needs, and build processes for data transformation and management. Preferred Qualifications: Proficient in building web applications using frameworks like Pydash, Plotly, R Shiny, Streamlit, Django, Dash, Python Flask, React.js, or Angular JS. Experienced with advanced AI and machine learning concepts including Deep Learning, Reinforcement Learning, Image Recognition, GenAI, and understanding the real-world application of various ML techniques. Strong knowledge of cloud environments and MLOps tools, including Databricks, Docker, Azure Data Factory, machine learning APIs (Azure, AWS, Vertex AI), Snowflake, and Google Cloud components (Cloud Build, Cloud Run, Kubernetes). Familiar with data visualization tools (Domo, Looker, Streamlit), working with third-party data (syndicated market data, Point of Sales), and has experience in Data Science roles within the CPG industry, ideally in relevant geographies. Our Commitment to Inclusion Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business. Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law. Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level About The Role We’re seeking an experienced and forward-thinking Lead AI Engineer to head the development of cutting-edge AI applications leveraging large language models (LLMs) and generative AI techniques. In this high-impact role, you will guide the architecture, deployment, and optimization of AI systems that power real-world, intelligent applications. You’ll be at the intersection of research and engineering, leading a team of top-tier AI engineers while shaping the future of AI capabilities within the organization. What You’ll Do Architect AI Solutions Design and lead the development of end-to-end AI systems that leverage LLMs, retrieval-augmented generation (RAG), and autonomous agent frameworks. Model Integration and Optimization Work hands-on with both open-source (Llama, Mistral, Falcon, etc.) and proprietary models (GPT-4, Claude, Gemini), fine-tuning them for specialized applications using proprietary data. Agentic Systems & RAG Build intelligent agents capable of reasoning, planning, and performing multi-step tasks using agentic architectures and RAG pipelines with vector databases like FAISS or Weaviate. Production-Grade Engineering Oversee scalable deployment, versioning, and monitoring of AI models in production using modern MLOps practices and cloud-native platforms (AWS, GCP, Azure). Cross-functional Collaboration Partner with data scientists, product managers, and software engineers to transform complex problems into elegant AI-driven products. AI Team Leadership Mentor a team of engineers, drive technical direction, and manage project priorities, sprint planning, and roadmap execution. Innovation & Research Stay ahead of the curve by tracking advancements in the AI/LLM space. Promote a culture of experimentation, rapid prototyping, and responsible AI. Ethics & Evaluation Implement best practices for model interpretability, bias mitigation, and responsible deployment of AI systems. Experience Must-Have Qualifications 5+ years of hands-on experience in AI/ML engineering with a primary focus on NLP and LLMs. Proven experience in designing and deploying production-grade AI systems. Technical Skills Strong command of Python and frameworks like PyTorch , TensorFlow , LangChain , and LlamaIndex . Solid knowledge of transformer architectures , embeddings, fine-tuning techniques, and tokenization. Experience integrating with vector databases (FAISS, Pinecone, Weaviate). Proficiency in designing APIs and working with distributed systems . Familiarity with MLOps , containerization (Docker), and orchestration tools (Kubernetes). Leadership Experience managing engineering teams and projects, with a track record of shipping successful AI solutions. Cloud & Deployment Deep experience with deploying AI systems on AWS , GCP , or Azure , and optimizing workloads for cost and performance. Nice-to-Have Experience working with multi-modal AI models (text, image, video, audio). Knowledge of RLHF (Reinforcement Learning from Human Feedback) methodologies. Contributions to open-source AI projects or peer-reviewed research. Prior experience at a startup or AI research lab . Show more Show less

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Science Architect · 2 to 3 years of experience in Generative AI solution development · Proven track record and experience with with GenAI technologies o Open source LLMs like Llama, Gemma, Mixtral etc o Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etc o Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT(LoRA, QLoRA ..) o Understanding of SLMs such as Phi3,QWEN, BERT and Transformer architecture o Vector databases like Pinecone, Qdrant etc. · Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model · Expertise with the following scripting languages: o Python, R, Tensorflow, Keras, Pytorch o OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs · Design and implement end-to-end Generative AI solutions, ensuring seamless integration with enterprise applications and workflows. · Lead technical evaluations and POCs (Proof of Concepts) to assess new AI models, frameworks, and vector databases for RAG solutions. · Develop scalable indexing and retrieval strategies to optimize search and generation performance in large-scale AI systems. · Implement hybrid search techniques, including dense and sparse retrieval, for enhanced information retrieval accuracy. · Define and enforce architectural standards, coding best practices, and performance benchmarks for RAG-based applications. · Collaborate with business leaders to identify AI-driven opportunities and develop strategic roadmaps for AI product evolution. · Drive the adoption of domain-specific AI solutions by tailoring RAG architectures to industry-specific requirements. · Establish feedback loops and model monitoring mechanisms to ensure continuous improvement of AI-generated outputs. · Utilize MLOps best practices to automate model deployment, monitoring, and retraining pipelines for Generative AI solutions. · Optimize knowledge graphs and vector embeddings to enhance contextual awareness in Graph RAG implementations. · Develop strategies for handling long-context retrieval and efficient chunking mechanisms for better AI response quality. · Leverage fine-tuning and reinforcement learning with human feedback (RLHF) to improve generative AI model performance. · Explore and integrate federated learning techniques to enable privacy-preserving AI model training and inference. · Conduct AI ethics assessments and bias mitigation strategies to ensure responsible AI development and deployment. · Engage with open-source AI communities and contribute to research publications or technical blogs on RAG advancements. · Participate in technical panels, conferences, and industry events to showcase AI expertise and thought leadership. · Support sales and pre-sales teams by providing technical guidance, solution demonstrations, and AI-driven business value assessments. · Establish AI Centers of Excellence (CoE) within the organization to drive innovation, knowledge sharing, and AI capability building. · Ensure compliance with enterprise security policies, data governance regulations, and responsible AI guidelines. · Develop multi-modal AI capabilities that integrate NLP, Computer Vision, and Speech Recognition for advanced generative applications. · Prior experience working on Mobility, Manufacturing or Healthcare domain will be a plus. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and asso Educational qualification: BE/BTech or MCA Experience : 10-15 years

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Scientist · 2 to 3 years of experience in Generative AI solution development · Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making. · Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments. · Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents. · Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows. · Hands-on experience integrating LLMs (GPT, LLaMA, Mistral, etc.) with agentic frameworks to enhance automation and reasoning. · Expertise in hierarchical agent frameworks, distributed agent coordination, and decentralized AI governance. · Strong grasp of memory architectures, tool use, and action planning within AI agents. · Autonomy Score: Measures the degree of independence in decision-making. · Collaboration Efficiency: Evaluates the ability of agents to work together and share information. · Task Completion Rate: Tracks the percentage of tasks successfully executed by agents. · Response Time: Measures the latency in agent decision-making and execution. · Adaptability Index: Assesses how well agents adjust to dynamic changes in the environment. · Resource Utilization Efficiency: Evaluates computational and memory usage for optimization. · Explainability & Interpretability Score: Ensures transparency in agent reasoning and outputs. · Error Rate & Recovery Time: Tracks failures and the system’s ability to self-correct. · Knowledge Retention & Utilization: Measures how effectively agents recall and apply information. · Hands-on experience with LLMs such as GPT, BERT, LLaMA, Mistral, Claude, Gemini, etc. · Proven expertise in both open-source (LLaMA, Gemma, Mixtral) and closed-source (OpenAI GPT, Azure OpenAI, Claude, Gemini) LLMs. · Advanced skills in prompt engineering, tuning, retrieval-augmented generation (RAG), reinforcement learning (RAFT), and LLM fine-tuning (PEFT, LoRA, QLoRA). · Strong understanding of small language models (SLMs) like Phi-3 and BERT, along with Transformer architectures. · Experience working with text-to-image models such as Stable Diffusion, DALL·E, and Midjourney. · Proficiency in vector databases such as Pinecone, Qdrant for knowledge retrieval in agentic AI systems. · Deep understanding of Human-Machine Interaction (HMI) frameworks within cloud and on-prem environments. · Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs. · Expertise in Python, R, TensorFlow, Keras, and PyTorch. · Hands-on experience with NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Knowledge Graphs, and LLM-based applications. · Proficiency in advanced statistical methods and transformer-based text processing. · Experience in reinforcement learning and planning techniques for autonomous agent behavior. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails · Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. · Experience in cloud services like Azure, GCP and AWS · Multi-agent frameworks: AutoGen, LangGraph, LangChain, CrewAI · Large Language Models (LLMs): GPT, Educational qualification: BE,BTECH or PHD

Job Description Location - Hyderabad/Gurgaon Experience - 4-8 years L2 Application Support Engineer - (Atlas reasoning engine) We at Publicis Sapient, enable our clients to thrive in Next and to create business value through expert strategies, customer-centric experience design, and world-class product engineering. The future of business is disruptive, transformative and becoming digital to the core. In our 20 + years in IT, never before have we seen such a dire need for transformation in every major industry - from financial services to automotive, consumer products, retail, energy, and travel. To make this transformative journey a reality in these exciting times, we seek Rockstars who will: Brave it out to go do the next; what will be from what is Exhibit the optimism that says there is no limit to what we can achieve deeply-skilled, bold, collaborative, flexible Reimagine the way the world works to help businesses improve the daily lives of people and the world. Our people thrive because of the belief that it is both our privilege and responsibility to usher our clients and the world into Next. Our work is fueled by challenging boundaries, multidisciplinary collaboration, highly agile teams, and the power of the newest technologies and platforms. If that's you, come talk to us! This is the world-class engineering team where you should build your career JOB PURPOSE This position is to provide to 2nd level of support for all application-level production environment issues, user support queries and requests. JOB RESPONSIBILITIES Below are key role and responsibilities for this position: Interact with L1 and keep run-books and Standard support operational procedures(SOP) up-to-date Perform Ad-hoc support tasks and prepare reports for business Troubleshoot all the new incidents/issues for which knowledge base is not available and escalated by L1 team Resolve the incidents/issues as per agreed SLA Address the service requests as per agreed SLA Follow the escalation process to escalate to L3 team or next level of support as per escalation metric if unable to resolve the issue within agreed time window Prepare the Incident post-mortem / RCA(Root cause analysis) report of incidents and share it with all the stakeholders within agreed timeline Perform the shift handover activities as per agreed SOPs Participate in problem management, change management, knowledge management, even management etc. Update knowledge base with new learnings, changes in resolution steps etc. in timely manner Ensure SLA/KPI (under control of L2 team like incident response time are met and collect/update data of it in required tools Help shift/team lead to prepare to various operational reports required by internal and external stakeholders Contribute to support reusable assets and internal knowledge sharing sessions Work to build-up skills for L3 support level Work on POC of different solutions, tools etc. POC Coordinate with L1 and L3 engineers (as per case requirement) on various issues, incidents, service requests, user queries, various changes in environment, various events etc. Work on automation of manual activities if possible and share the details of automation opportunities with L3 team Personal Attributes: Systematic problem-solving approach, coupled with effective communication skills and a sense of drive Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution Should be flexible to work in all shifts Ability to prioritize when under pressure SKILL REQUIREMENTS Must Skills Hands-on experience with Salesforce s Atlas Reasoning Engine . Ability to troubleshoot and support AI agent workflows powered by Atlas, including task orchestration and decision-making logic. Familiarity with System 2 reasoning models, reinforcement learning feedback loops, and graph-based architectures. Experience monitoring and optimizing autonomous agent performance in production environments. Proficiency in analyzing logs and telemetry data from Atlas-powered agents to identify and resolve issues. Understanding of event-driven systems and asynchronous task execution in enterprise AI platforms. Ability to collaborate with AI/ML teams to escalate and resolve complex reasoning or orchestration issues. Exposure to Agentforce or similar AI agent ecosystems is a strong plus Familiarity and working experience on ecommerce projects Working knowledge with ServiceNOW ITSM tool Knowledge of Production Support processes and procedures. Have ability to demonstrate functional and technical architecture knowledge and correlate between the two from past experiences Have good exposure of ITIL Processes like Incident Management, Problem Management, and Knowledge Management etc. Nice to have Skills Good understanding of Accessibility and comfortable using dev tool bar for debugging. Have some exposure of cloud technologies Have understanding of how cloud infrastructure is setup, applications are deployed, various services are setup and used etc. Have ability to understand the technical errors in the application log and understand the solutions provided by L3/Development teams at least at high level

Engineering Gurgaon, India Publicis Sapient Intermediate Hybrid 6/18/2025 111925 EnrichPlusP250611112541 Overview Location - Hyderabad/Gurgaon Experience - 4-8 years L2 Application Support Engineer – (Atlas reasoning engine) We at Publicis Sapient, enable our clients to thrive in Next and to create business value through expert strategies, customer-centric experience design, and world-class product engineering. The future of business is disruptive, transformative and becoming digital to the core. In our 20 + years in IT, never before have we seen such a dire need for transformation in every major industry - from financial services to automotive, consumer products, retail, energy, and travel. To make this transformative journey a reality in these exciting times, we seek Rockstars who will: Brave it out to go do the next; “what will be” from “what is” Exhibit the optimism that says there is no limit to what we can achieve deeply-skilled, bold, collaborative, flexible Reimagine the way the world works to help businesses improve the daily lives of people and the world. Our people thrive because of the belief that it is both our privilege and responsibility to usher our clients and the world into Next. Our work is fueled by challenging boundaries, multidisciplinary collaboration, highly agile teams, and the power of the newest technologies and platforms. If that’s you, come talk to us! This is the world-class engineering team where you should build your career JOB PURPOSE This position is to provide to “2nd level of support” for all application-level production environment issues, user support queries and requests. JOB RESPONSIBILITIES Below are key role and responsibilities for this position: Interact with L1 and keep run-books and Standard support operational procedures(SOP) up-to-date Perform Ad-hoc support tasks and prepare reports for business Troubleshoot all the new incidents/issues for which knowledge base is not available and escalated by L1 team Resolve the incidents/issues as per agreed SLA Address the service requests as per agreed SLA Follow the escalation process to escalate to L3 team or next level of support as per escalation metric if unable to resolve the issue within agreed time window Prepare the Incident post-mortem / RCA(Root cause analysis) report of incidents and share it with all the stakeholders within agreed timeline Perform the shift handover activities as per agreed SOPs Participate in problem management, change management, knowledge management, even management etc. Update knowledge base with new learnings, changes in resolution steps etc. in timely manner Ensure SLA/KPI (under control of L2 team like incident response time are met and collect/update data of it in required tools Help shift/team lead to prepare to various operational reports required by internal and external stakeholders Contribute to support reusable assets and internal knowledge sharing sessions Work to build-up skills for L3 support level Work on POC of different solutions, tools etc. POC Coordinate with L1 and L3 engineers (as per case requirement) on various issues, incidents, service requests, user queries, various changes in environment, various events etc. Work on automation of manual activities if possible and share the details of automation opportunities with L3 team Personal Attributes: Systematic problem-solving approach, coupled with effective communication skills and a sense of drive Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution Should be flexible to work in all shifts Ability to prioritize when under pressure SKILL REQUIREMENTS Must Skills Hands-on experience with Salesforce's Atlas Reasoning Engine . Ability to troubleshoot and support AI agent workflows powered by Atlas, including task orchestration and decision-making logic. Familiarity with System 2 reasoning models, reinforcement learning feedback loops, and graph-based architectures. Experience monitoring and optimizing autonomous agent performance in production environments. Proficiency in analyzing logs and telemetry data from Atlas-powered agents to identify and resolve issues. Understanding of event-driven systems and asynchronous task execution in enterprise AI platforms. Ability to collaborate with AI/ML teams to escalate and resolve complex reasoning or orchestration issues. Exposure to Agentforce or similar AI agent ecosystems is a strong plus Familiarity and working experience on ecommerce projects Working knowledge with ServiceNOW ITSM tool Knowledge of Production Support processes and procedures. Have ability to demonstrate functional and technical architecture knowledge and correlate between the two from past experiences Have good exposure of ITIL Processes like Incident Management, Problem Management, and Knowledge Management etc. Nice to have Skills Good understanding of Accessibility and comfortable using dev tool bar for debugging. Have some exposure of cloud technologies Have understanding of how cloud infrastructure is setup, applications are deployed, various services are setup and used etc. Have ability to understand the technical errors in the application log and understand the solutions provided by L3/Development teams at least at high level

Software Engineer, AI Train large-language models (LLMs) to write production-grade code: Compare & rank multiple code snippets, explaining which is best and why. Repair & refactor AI-generated code for correctness, efficiency, and style. Inject feedback (ratings, edits, test results) into the RLHF pipeline and keep it running smoothly. End result: the model learns to propose, critique, and improve code the way you do. RLHF in one line Generate code ➜ expert engineers rank, edit, and justify ➜ convert that feedback into reward signals ➜ reinforcement learning tunes the model toward code you’d actually ship. What is Needed 4+ years of professional software-engineering experience. Extreme attention to detail and excellent writing skills—most of the job is explaining why one solution is better than another. This requirement cannot be overstated! You actually enjoy reading documentation and specs. Proven ability to thrive in a fully asynchronous, low-oversight remote environment. Strong code-review instincts: can spot logic errors, performance traps, and security issues quickly. What is Not Needed No prior RLHF or AI-training experience required. You don’t need deep machine-learning knowledge—if you can review code and explain your reasoning, we’ll teach you the RLHF bits. Tech Stack We are looking for Fullstack JavaScript or TypeScript engineers React, Next.js Node Postgress Logistics Location: Fully remote (work from anywhere). Hours: Minimum 15 hrs/week with the ability to work up to 40 hours per week Engagement: 1099 contract Straightforward impact, zero fluff. If this fits your profile, apply here.