59 Mlops Practices Jobs

As an innovative and highly skilled AI/ML Specialist, your role will involve designing, developing, and deploying advanced machine learning and artificial intelligence solutions to tackle complex business challenges. You should have expertise in machine learning algorithms, deep learning frameworks, and AI model deployment, along with the ability to work with large datasets to deliver impactful, scalable solutions. **Key Responsibilities:** - Design, develop, and optimize machine learning and deep learning models for various use cases. - Collect, preprocess, and analyze structured and unstructured datasets to prepare them for model training. - Select appropriate algorithms and techniques based on problem requirements and business objectives. - Build end-to-end AI/ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment. - Implement and optimize models using frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn. - Deploy models into production environments using cloud platforms (AWS SageMaker, Azure ML, GCP AI Platform) or on-premises solutions. - Monitor, maintain, and retrain models to ensure long-term accuracy and performance. - Collaborate with cross-functional teams to integrate AI/ML solutions into products and workflows. - Stay updated with the latest advancements in AI, ML, NLP, and computer vision to drive innovation. **Required Technical Skills:** - Strong programming skills in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). - Solid understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers). - Experience with NLP frameworks (Hugging Face, SpaCy, NLTK) and/or Computer Vision libraries (OpenCV, YOLO, Detectron). - Proficiency in data wrangling and feature engineering for high-quality datasets. - Knowledge of model deployment strategies using APIs, containers (Docker), and orchestration tools (Kubernetes). - Familiarity with big data tools (Spark, Hadoop) for large-scale data processing. - Understanding of MLOps practices, CI/CD pipelines, and model monitoring tools. **Preferred Qualifications:** - Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. - Experience in domain-specific AI (healthcare, finance, manufacturing, etc.). - Exposure to generative AI models (LLMs, Stable Diffusion, GPT-based systems). - Understanding of data privacy and AI ethics. As an AI/ML Specialist, you should exhibit strong problem-solving and analytical skills, excellent communication and presentation abilities, and the ability to work collaboratively in cross-functional teams. A passion for continuous learning and innovation will be key to success in this role.,

As a recent PhD graduate in Computer Science, Machine Learning, AI, or a related field, you have the opportunity to join a cutting-edge team that focuses on pushing the boundaries of machine learning in a dynamic industry setting. In this role, you will work on complex challenges related to large language models (LLMs), optical character recognition (OCR), and model scaling. **Key Responsibilities:** - Lead research initiatives to enhance OCR accuracy across various document types and languages. - Train and fine-tune LLMs using domain-specific data to improve performance in specialized contexts. - Develop efficient techniques to scale LLMs for high-volume production environments. - Design and implement innovative approaches to model optimization and evaluation. - Collaborate with cross-functional teams to integrate AI solutions into production systems. - Stay updated with the latest research and incorporate state-of-the-art techniques. - Document methodologies, experiments, and findings for technical and non-technical audiences. **Required Qualifications:** - PhD in Computer Science, Machine Learning, AI, or a related field completed within the last year. - Strong understanding of deep learning architectures, particularly transformer-based models. - Experience with OCR systems and techniques for enhancing text recognition accuracy. - Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX). - Demonstrated ability to implement and adapt research papers into working code. - Excellent problem-solving skills with a methodical approach to experimentation. - Strong communication skills to explain complex technical concepts clearly. **Preferred Qualifications:** - Research focus during PhD in areas relevant to NLP, computer vision, multimodal learning. - Familiarity with distributed training systems for large-scale models. - Experience with model quantization, pruning, and other efficiency techniques. - Understanding of evaluation methodologies for assessing model performance. - Knowledge of MLOps practices and tools for model deployment. - Publications at top-tier ML conferences (NeurIPS, ICML, ACL, CVPR, etc.). FourKites is the leader in AI-driven supply chain transformation for global enterprises, offering an ideal transition from academic research to industry application. You will benefit from a structured onboarding program, work on frontier AI models with real-world impact, and have access to significant computing resources. Additionally, you can enjoy a collaborative environment, flexible work arrangements, competitive compensation, and support for continued professional development and conference attendance. **Benefits:** - Medical benefits from the first day of employment. - 36 PTO days (Sick, Casual, and Earned), 5 recharge days, 2 volunteer days. - Home office setups and technology reimbursement. - Lifestyle and family benefits. - Annual swags/festive swags. - Ongoing learning and development opportunities (Professional development program, Toast Master club, etc.).,

As an AI Integration Engineer at our company in Ahmedabad, your role will involve deploying and integrating AI/ML models into production environments to ensure scalability, reliability, and security. You will collaborate with various teams to streamline AI adoption and maximize the impact of our AI-driven solutions. Key Responsibilities: - Collaborate with AI/ML teams to deploy machine learning models into applications and services. - Design and implement APIs, SDKs, and microservices to facilitate seamless AI model consumption. - Maintain high availability, scalability, and security of AI services in production. - Implement CI/CD pipelines, observability tools, and monitoring systems to track and enhance model performance. - Develop automated pipelines for model retraining, versioning, and rollback. - Apply caching strategies, model compression, and other techniques to optimize inference speed and system efficiency. - Work with cloud platforms (AWS, GCP, Azure) and support hybrid setups (cloud + on-prem). - Partner with DevOps, software engineers, and product teams to smoothly integrate AI capabilities into products and services. Required Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - 3 - 6 years of experience in software engineering, backend development, or MLOps. - Proficiency in Python with experience using FastAPI, Flask, or Django. - Experience integrating ML models with tools like TensorFlow Serving, TorchServe, ONNX, or custom model wrappers. - Hands-on experience with Docker, Kubernetes, and container orchestration. - Understanding of CI/CD pipelines, MLOps practices, and model lifecycle management. - Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services. - Excellent English communication skills to collaborate with cross-functional teams and present technical solutions clearly.,

You will be working in a leading player in the medical communications and knowledge management industry, with headquarters in Bangalore and presence in 5 locations outside India. As the ideal candidate, you will lead and manage the AI development team to deliver scalable and production-ready solutions. Your responsibilities will include conducting research to determine the best AI models, developing proofs of concept (PoCs), providing technical leadership, collaborating with stakeholders, driving recruitment and training, defining AI architecture and technical roadmap, owning end-to-end lifecycle of AI feature development, establishing MLOps practices, and ensuring compliance with data privacy regulations and ethical AI practices. Qualifications required for this role include a Bachelor's degree in Computer Science, Engineering, or Mathematics, 5+ years of relevant experience, advanced knowledge of leading architecture solutions, strong interpersonal and collaboration skills, and the ability to demonstrate technical concepts to non-technical audiences.,

As a highly skilled GenAI Lead Engineer, your role will involve designing and implementing advanced frameworks for alternate data analysis in the investment management domain. You will leverage LLM APIs (such as GPT, LLaMA, etc.), build scalable orchestration pipelines, and architect cloud/private deployments to drive next-generation AI-driven investment insights. Additionally, you will lead a cross-functional team of Machine Learning Engineers and UI Developers to deliver robust, production-ready solutions. **Key Responsibilities:** - **GenAI Framework Development:** Develop custom frameworks using GPT APIs or LLaMA for alternate data analysis and insights generation. Optimize LLM usage for investment-specific workflows, including data enrichment, summarization, and predictive analysis. - **Automation & Orchestration:** Design and implement document ingestion workflows using tools such as n8n (or similar orchestration frameworks). Build modular pipelines for structured and unstructured data. - **Infrastructure & Deployment:** Architect deployment strategies on cloud (AWS, GCP, Azure) or private compute environments (CoreWeave, on-premises GPU clusters). Ensure high availability, scalability, and security in deployed AI systems. **Qualification Required:** - Strong proficiency in Python with experience in frameworks such as TensorFlow or PyTorch. - 2+ years of experience in Generative AI and Large Language Models (LLMs). - Experience with VectorDBs (e.g., Pinecone, Weaviate, Milvus, FAISS) and document ingestion pipelines. - Familiarity with data orchestration tools (e.g., n8n, Airflow, LangChain Agents). - Understanding of cloud deployments and GPU infrastructure (CoreWeave or equivalent). - Proven leadership skills with experience managing cross-functional engineering teams. - Strong problem-solving skills and ability to work in fast-paced, data-driven environments. - Experience with financial or investment data platforms. - Knowledge of RAG (Retrieval-Augmented Generation) systems. - Familiarity with frontend integration for AI-powered applications. - Exposure to MLOps practices for continuous training and deployment.,

Key Responsibilities Develop lightweight Python-based accelerators, validators, and utility components that support automation use case validation and edge-case testing. Build diagnostic tools and reference implementations for integration scenarios (e.g., document parsing, API response emulation) to assist internal teams in early-phase feasibility nvalidation. Create reusable code snippets and utility libraries for functions that are not available in standard RPA/AI platforms, ensuring clear handover boundaries. Support internal teams with troubleshooting technical blockers and provide fallback logic examples. Develop Python modules tailored to internal validation, diagnostic, or transformation needs, such as document parsing pipelines, mock API responders, or reusable data handling routines for pre-processing automation input data. Work on No Code / Low Code platforms for Agentic development (on a need basis). Maintain internal reference repository of vetted Python tools for common preprocessing tasks (e.g., tabular extraction, NLP tokenization, batch transformation). Review Python-based components delivered by SI (where applicable) for adherence to internal coding standards, logging protocols, and modularity expectations. Assist in operationalizing post-deployment enhancements (non-functional) such as optimization of retry logic, timeout handling, or enrichment utilities. May lead a small team of 3 to 4 Python developers supporting internal engineering needs. Required Technical Skills Proficiency in Python programming with focus on scripting, utility design, and code modularization. Experience in API integration, including request handling, response parsing, and mocking. Ability to design reusable automation components and diagnostics for validation workflows. Knowledge of cloud function readiness (e.g., Azure Functions, AWS Lambda). Strong foundation in exception handling and reliability engineering Azure AI based development experience Full-stack Development Capability: Ability to design and implement both front-end user interfaces (UIs) and back-end services for automation and validation tools. This includes: 1. Developing responsive and intuitive UIs using frameworks such as React, Angular, or simple web-based forms. 2. Building robust Python-based back-end modules, APIs, and services. 3. Ensuring seamless integration with authentication, error handling, and logging. 4. Experience in building CI/CD pipelines and deploying on cloud. 5. Experience in deploying containerized workloads (AKS, Azure Kubernetes Services or similar). Preferred Skills 1. Exposure to natural language processing (NLP) and document transformation workflows. 2. Experience working in enterprise environments with structured development and logging practices. 3. Understanding of the boundaries between internal tools and vendor-delivered solutions. Soft Skills 1. Ability to work independently on utility design and diagnostic component development. 2. Strong collaboration skills to support PoC teams and interface with solution integrators. 3. Proactive debugging and root cause analysis approach. 4. Clear Deliverables 1. Reusable Python code libraries, scripts, and internal tooling assets. 2. Diagnostic modules for integration scenarios and edge-case testing. 3. Reference repository of vetted preprocessing scripts. 4. Review notes and improvement recommendations for SI-delivered Python components. Inte

Job Description :We are looking for a skilled and proactive Machine Learning Engineer with a strong foundation in Python and SQL, and hands-on experience with modern MLOps tools and practices. You will be responsible for building, deploying, and maintaining scalable machine learning solutions in production environments, leveraging cloud-native technologies and automation pipelines. Key Responsibilities: Design and implement end-to-end machine learning pipelines. Develop and deploy ML models using Python and manage data workflows using SQL . Build and orchestrate workflows using Google Cloud Composer (Airflow) . Containerize applications using Docker and deploy them on Google Kubernetes Engine (GKE) . Set up and manage CI/CD pipelines for automated model training and deployment. Develop and maintain RESTful APIs to serve ML models in production. Collaborate with data scientists, data engineers, and DevOps teams to ensure seamless integration and scalability. Required Skills & Qualifications: Proficiency in Python and SQL for data manipulation and model development. Experience with Google Cloud Platform (GCP) , especially GKE , Composer , and BigQuery . Strong understanding of MLOps practices and tools. Hands-on experience with Docker and container orchestration using Kubernetes . Experience with CI/CD tools (e.g., GitHub Actions, Jenkins, Cloud Build). Proficiency in API development using frameworks like Flask or FastAPI . Familiarity with version control systems (e.g., Git).

You are an experienced Senior Consultant with a strong background in Java development and practical exposure to Generative AI (GenAI) technologies. Your main responsibilities will include designing and delivering scalable solutions, integrating AI-driven capabilities into enterprise applications, and providing technical leadership to development teams. Your key responsibilities will involve designing, developing, and maintaining scalable applications using Java, Spring Boot, and Microservices. You will also be responsible for architecting and integrating Generative AI solutions such as LLMs, embeddings, and RAG pipelines into business applications. Collaborating with data scientists and AI engineers to operationalize models, developing and optimizing APIs for AI/ML services, and ensuring secure and efficient integration will be crucial aspects of your role. Additionally, implementing cloud-native solutions on platforms like AWS, Azure, or GCP will be part of your responsibilities. You will play a significant role in guiding and mentoring junior engineers, conducting code reviews, and knowledge-sharing sessions. Collaborating with business stakeholders to translate requirements into technical architecture and solutions will be essential. Ensuring that delivery aligns with best practices in software engineering, CI/CD, testing, and TDD/BDD will also be a key part of your responsibilities. To excel in this role, you must have at least 9 years of strong development experience in Java, Spring Boot, and Microservices. Hands-on experience with Generative AI/LLMs, a strong understanding of RESTful APIs, GraphQL, and event-driven architectures, as well as experience with cloud services like AWS Lambda, S3, DynamoDB, GCP Vertex AI, or Azure Cognitive Services are required. Exposure to vector databases, familiarity with prompt engineering and AI model fine-tuning, and a solid understanding of data pipelines and integrating AI services into enterprise workflows are also essential. You should have a strong grasp of software engineering best practices such as TDD, CI/CD, and Agile methodologies. It would be beneficial if you have experience in Python for AI/ML integrations, familiarity with Kubernetes, Docker, Terraform for deployment, knowledge of MLOps practices, and prior consulting experience in digital transformation or AI-led initiatives.,

The Data Analyst role at our organization is a pivotal position that involves transforming intricate challenges into actionable insights by harnessing the power of data. As a Data Analyst, you will work collaboratively with diverse teams to analyze extensive datasets, construct predictive models, and devise data-centric solutions that elevate strategic decision-making processes and propel organizational advancement. We seek an inquisitive, imaginative individual who is enthusiastic about utilizing statistical and machine learning methodologies to address real-world issues. This role demands a proactive approach, strong implementation capabilities, and the capacity to operate autonomously. In addition to executing the existing strategy, you will be expected to contribute to its evolution. We are in search of candidates who aspire to make contributions to the broader data architecture community and emerge as thought leaders in this field. Embracing a diversity of perspectives is a core value for us, and we are dedicated to assembling a team that mirrors the diversity of our global community. Your responsibilities will include collecting, processing, and analyzing substantial volumes of structured and unstructured data from various sources. Your insights will play a key role in guiding strategic decisions and enhancing technology operations and metrics. This will involve improving resource utilization, enhancing system reliability, and reducing technical debt. Close collaboration with business stakeholders will be essential to grasp their objectives, formulate analytical questions, and translate requirements into data-driven solutions. Engaging in exploratory data analysis (EDA) to reveal patterns, trends, and actionable insights will be a crucial aspect of your work. Furthermore, you will be tasked with visualizing and communicating findings through engaging reports, dashboards, presentations, and data storytelling techniques tailored to both technical and non-technical audiences. Working closely with engineering teams, you will deploy predictive models into production environments, ensuring their reliability, scalability, and performance. Continuous monitoring, evaluation, and enhancement of model performance will be part of your ongoing responsibilities, requiring you to implement improvements as needed. Staying abreast of the latest research, tools, and best practices in data science, machine learning, and artificial intelligence is integral to this role. Additionally, fostering a culture of experimentation, continuous learning, and innovation within the organization is a key expectation. To be successful in this role, you should possess at least 10 years of experience as a practitioner in data engineering or a related field, along with a Bachelor's or Master's degree in computer science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field. Strong programming skills in languages like Python or R, familiarity with SQL, and knowledge of distributed computing frameworks such as Spark and Hadoop are advantageous. Proficiency in data visualization tools like Matplotlib, PowerBI, and Tableau is required. A solid grasp of probability, statistics, hypothesis testing, and data modeling concepts is essential. Experience with cloud platforms (e.g., AWS, GCP, Azure) for data storage, processing, and model deployment is beneficial. Excellent communication and collaboration skills are a must, including the ability to explain complex technical concepts to diverse audiences. Strong attention to detail, analytical thinking, and problem-solving abilities are also key attributes for this role. Preferred qualifications include experience in large-scale data science projects or in industry domains like finance, healthcare, retail, or technology. Familiarity with MLOps practices, model versioning, monitoring tools, natural language processing (NLP), computer vision, or time-series analysis is advantageous. Contributions to open-source projects or publications in relevant conferences/journals are a plus. Developing and maintaining data pipelines, ETL processes, and implementing machine learning algorithms and statistical models aimed at analyzing technology metrics are additional preferred qualifications. Hands-on experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, Keras, PyTorch, or XGBoost is desirable. Key competencies for this role include analytical expertise, technical proficiency in machine learning, statistical modeling, and data engineering principles, effective communication skills, collaboration abilities, and a dedication to innovative problem-solving and experimentation with novel technologies.,

As a Senior Solution Architect specializing in Snowflake AI, you will play a crucial role in shaping the future of AI-driven data architecture on Snowflake and cloud platforms. With over 10 years of experience in architecture and data engineering, including a minimum of 4 years of hands-on expertise with Snowflake, you will lead the definition of technical vision, integration strategy, and end-to-end architecture for Snowflake-based AI/ML solutions that drive advanced analytics, data science, and enterprise decision-making. In this leadership position, you will be responsible for designing and delivering scalable, secure, and automated data platforms on Snowflake. Your role will involve driving the adoption of best practices in data modeling, AI/ML integration, automated testing, and DevOps for data while collaborating closely with stakeholders from engineering, product, and business functions. Your key responsibilities will include defining and leading the architecture vision and roadmap for Snowflake-based AI/ML solutions, designing end-to-end data and AI pipelines, establishing frameworks for automated code quality and testing, partnering with cross-functional teams to ensure seamless solution delivery, driving ETL/ELT modernization, ensuring data governance, security, and compliance with regulatory standards, providing technical leadership and guidance to engineering teams, evaluating emerging technologies, and serving as a trusted advisor for stakeholders and C-level leadership. To excel in this role, you should possess at least 10 years of experience in solution architecture, with a minimum of 4 years of direct expertise with Snowflake. You should have a proven track record in designing cloud-native architectures on leading cloud platforms such as AWS, Azure, or GCP, deep knowledge of ETL/ELT pipelines, AI/ML model integration, and MLOps practices, expertise in various Snowflake features, a strong understanding of data governance, lineage, and security frameworks, proficiency in SQL, Python, and data modeling best practices, excellent communication and stakeholder management skills, and the ability to influence at all levels. Preferred qualifications for this role include experience in implementing AI/ML-driven solutions in credit, risk, or financial domains, hands-on experience with related technologies like Databricks, Apache Spark, Airflow, or Trino, knowledge of data visualization and BI tools, background in data platform modernization or migration to Snowflake, and experience in solution design for highly regulated industries. This is an onsite role with relocation support available depending on project and business needs.,

As a First Responder AI Expert with 5-7 years of experience, your primary responsibility will be to lead the development of AI agents designed for instant, context-aware responses. This role requires expertise in AI engineering, natural language processing (NLP), and a deep understanding of business operations. You will play a crucial role in creating, deploying, and optimizing AI agents that act as a "first responder" to various queries and events within the organization. This includes automating support, knowledge access, and operational workflows to enhance efficiency and productivity. Your key responsibilities will involve end-to-end agent development, where you will design, develop, and deploy conversational and autonomous AI agents capable of triaging, answering, and resolving user requests in real-time. Leveraging large language models (LLMs) and implementing robust RAG (Retrieval Augmented Generation) systems will be essential to ensure accurate and effective agent responses. Additionally, you will be required to integrate AI agents with internal business systems such as Slack, Jira, Salesforce, and CRM using APIs, enabling autonomous actions and seamless workflow automation. Your prompt engineering and agent design skills will be crucial in ensuring agents provide relevant and contextually appropriate responses while delivering a positive user experience. Collaboration and leadership are also key aspects of this role, as you will act as a subject matter expert on "first responder" AI solutions, provide technical guidance to cross-functional teams, and work closely with product managers and business stakeholders to define agent capabilities. Mentoring junior engineers and sharing best practices in agent development will also be part of your responsibilities. To be successful in this role, you must hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, along with 5-7 years of experience in AI engineering, NLP engineering, or a similar role. Strong proficiency in Python is non-negotiable, and deep expertise in NLP techniques, generative AI technologies, MLOps practices, cloud platforms, and system integration is required. Preferred qualifications include experience with specific agent frameworks, developing AI solutions for various business functions, understanding of ethical AI principles, contributions to open-source projects, and familiarity with real-time streaming data technologies. If you are a highly experienced and innovative AI professional looking to lead the development of cutting-edge AI solutions as a First Responder AI Expert, we invite you to apply and be part of our dynamic team.,

Techvantage Analytics is a fast-growing AI services and product engineering company specializing in Analytics, Machine Learning, and AI-based solutions. We are seeking a forward-thinking and highly experienced Gen AI Architect to design and implement cutting-edge AI solutions. The role involves leveraging the latest advancements in artificial intelligence and data science, including foundation models, multimodal AI, federated learning, and emerging AI frameworks. The ideal candidate will drive the development and deployment of scalable AI systems that power innovative applications across diverse domains. In this role, you will be responsible for AI Architecture Design, where you will develop robust architectures for generative AI solutions, leveraging the latest advancements in foundation models, large language models (LLMs), and multimodal AI. You will also be involved in Model Development, building and fine-tuning advanced generative models, such as GPT-based models, diffusion models, and transformers, for applications in text, image, video, and audio generation. Framework Integration is another key aspect of the role, where you will integrate modern AI frameworks, such as LangChain and LlamaIndex, to enhance the capabilities of generative models in production environments. Additionally, you will be tasked with implementing Data Strategy, including synthetic data generation, federated learning, and secure data sharing protocols for effective model training. You will design and oversee the deployment of scalable AI systems using the latest technologies, such as MLOps pipelines, container orchestration (Docker, Kubernetes), and serverless architectures. Ensuring Ethics & Compliance is also crucial, where you will make sure AI models comply with ethical guidelines, including responsible AI principles, addressing fairness, transparency, and mitigating bias. Staying updated with the latest AI trends, such as reinforcement learning with human feedback (RLHF), AI explainability, and continual learning, and applying them to real-world problems is essential. Collaboration is key in this role, as you will work closely with cross-functional teams, including data engineers, scientists, and product managers, to align AI systems with business goals. Leadership & Mentorship are also important aspects, as you will provide guidance to junior AI practitioners and foster a culture of innovation within the team. Performance Monitoring is another critical responsibility, where you will define KPIs for model performance, monitor systems in production, and implement mechanisms for continuous improvement and retraining. The ideal candidate for this role should have a Bachelors, Masters, or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or related fields, along with 5+ years of experience in AI/ML, with a focus on generative AI technologies. Proven expertise in deploying large-scale generative models in production environments, hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers, and proficiency in Python, R, or Julia for data science and AI model development are required. Additionally, expertise in cloud-native AI solutions, familiarity with advanced data strategies like synthetic data creation and federated learning, and hands-on experience with MLOps practices are preferred. Strong analytical skills, the ability to thrive in a dynamic, fast-paced environment, and a proven track record of working effectively within cross-functional teams are also desired qualities in the ideal candidate.,

About the Organization: An innovative AI company that provides intelligent business automation solutions, empowering organizations with AI-driven tools to streamline operations, enhance efficiency, and accelerate digital transformation. Headquartered in the U.S., with offices in India. Expectations: The ideal candidate will have a strong background in building B2B SaaS applications using Java, Spring, and Angular or React for the frontend. This role requires extensive experience across the full stack engineering spectrum, a deep understanding of cloud platforms such as AWS and GCP, and proficiency in system and network architecture. Additionally, the candidate should have hands-on experience with cloud infrastructure for application deployment and an understanding of integrating and hosting machine learning models. Key Responsibilities: Strategic Leadership: Develop and execute the engineering strategy that aligns with the company's vision, goals, and business objectives. Technical Leadership & Operations: Own Product Development, Champion customer-centric development practices, ensuring that all engineering efforts are focused on delivering value and building trust with customers. Machine Learning Integration: Collaborate with data scientists to integrate and host machine learning models within applications, implementing MLOps practices. Cloud & Infrastructure Management: Drive, Design and implement robust system and network architectures utilizing AWS and GCP to build scalable, reliable cloud solutions. Deploy and manage applications on Kubernetes, ensuring optimal performance and scalability. Handle traffic routing with Ingress Controllers (Nginx), oversee Certificate Management using Cert Manager, and manage secrets with Sealed Secrets and Vault. Qualifications: Education & Experience: Bachelors or Masters degree in Computer Science, Engineering, or a related field. Proven experience in software engineering, with a strong focus on B2B SaaS applications. At least 5 years of experience in a leadership role, preferably at the VP level.,

You will be a part of Bain Capability Network's Gurgaon office, specifically in the Data and Technology team, focusing on the Benchmarking team within the Data & Insights Industries CoE. Your primary responsibility will involve contributing to advancing Bain's expertise in the consumer products sector by developing and maintaining databases containing industry benchmarks and performance metrics. These data assets are crucial in providing Bain's consultants with valuable insights to drive client value in the consumer products industry. Furthermore, you will play a key role in creating intellectual property (IP) essential for new CPG cases globally at Bain. Your role will require you to translate business objectives into data and analytics solutions, utilizing various tools such as Gen AI, Scikit-Learn for machine learning models, and Hugging Face for NLP models. Collaborating with engineering and practice teams, you will be involved in designing scalable products, developing repeatable data processes, and staying updated on AI/ML technologies and best practices. Key responsibilities also include leading a small team, managing day-to-day activities, providing status updates, and creating standard operating procedures for data processes. A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related fields is preferred, along with 3+ years of experience in data science and engineering. Proficiency in Python or R, experience with AI/GenAI tools, RESTful and GraphQL APIs, MLOps practices, Git, and containerization is beneficial. Strong interpersonal and communication skills, along with the ability to explain technical concepts to a business audience, are essential for this role. Familiarity with Agile practices and Microsoft Office suite is preferred. Overall, you will play a vital role in enhancing Bain's capabilities in the consumer products sector through data-driven insights, innovative solutions, and advanced analytics. Your contributions will directly impact Bain's strategic guidance to clients and ensure excellence in the delivery of services.,

Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power wireless connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the worlds most highly integrated SoCs, Silicon Labs provides device makers the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over 16 countries and is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. Learn more at www.silabs.com. The Role As a Senior QA Engineer in the AI/ML team at Silicon Labs, you will play a pivotal role in defining and upholding quality standards for machine learning and deep learning models deployed on IoT edge devices. Based at our Hyderabad Software Centre of Excellence, you will design automated test frameworks, validate model performance under real-world conditions, and ensure seamless integration of AI technologies into next-generation IoT products. Meet the Team Youll be part of Silicon Labs newly established AI/ML SQA team, working at the forefront of innovation to deliver intelligent IoT solutions. The team collaborates closely with ML developers, DevOps, and product engineers across geographies to support the development, testing, and deployment of ML models and data pipelines. This team is responsible for building the foundation of quality assurance for ML models, enabling cutting-edge IoT products powered by artificial intelligence. Responsibilities : Develop and execute test strategies for machine learning, deep learning, and Tiny LLM models running on IoT edge devices. Validate model accuracy, robustness, and scalability under real-world IoT data conditions. Design automated frameworks to test data pipelines, feature extraction, inference performance, and edge/cloud integration. Ensure seamless integration of ML/DL modules into the IoT platform software stack (firmware, middleware, connectivity, and cloud APIs). Collaborate with ML developers to ensure models meet production-grade quality standards. Work with DevOps engineers to integrate ML model validation into CI/CD workflows. Requirements : Bachelors degree in Electrical Engineering or Computer Science (or equivalent combination of education and experience. 5+ Years of relevant industry experience Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, scikit-learn. Experience in designing and executing automated test frameworks for ML/DL systems. Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI. Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU). Knowledge of MLOps practices, including model versioning and deployment workflows. Understanding of natural language processing and Tiny LLMs is a plus. Benefits & Perks At Silicon Labs, youll be part of a highly skilled team where every engineer makes a meaningful impact. We promote work-life balance and a welcoming, fun environment. Equity Rewards (RSUs) Employee Stock Purchase Plan (ESPP) Insurance plans with outpatient cover National Pension Scheme (NPS) Flexible work policy Childcare support Silicon Labs is an equal opportunity employer and values the diversity of our employees. Employment decisions are made on the basis of qualifications and job-related criteria without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other characteristic protected by applicable law. Show more Show less

We are looking for a talented individual who has recently completed their PhD to join our cutting-edge team. This position is specifically tailored for fresh PhD graduates who are eager to apply their research expertise in a dynamic industry setting. In this role, you will be tasked with tackling complex challenges in large language models (LLMs), optical character recognition (OCR), and model scaling. You will have the opportunity to be at the forefront of developing and optimizing AI systems that push the boundaries of what's possible in machine learning. As part of your responsibilities, you will lead research initiatives aimed at enhancing OCR accuracy across diverse document types and languages. You will also work on training and fine-tuning LLMs using domain-specific data to improve performance in specialized contexts. Additionally, you will be involved in developing techniques to efficiently scale LLMs for high-volume production environments, as well as designing and implementing novel approaches to model optimization and evaluation. Collaboration with cross-functional teams to integrate AI solutions into production systems will be a key aspect of this role. It is important to stay current with the latest research and incorporate state-of-the-art techniques into your work. Documenting methodologies, experiments, and findings for both technical and non-technical audiences will also be part of your responsibilities. To qualify for this role, you must have a PhD in Computer Science, Machine Learning, AI, or a related field completed within the last year. A strong understanding of deep learning architectures, particularly transformer-based models, is required. Experience with OCR systems and techniques for improving text recognition accuracy is essential. Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX is a must. Demonstrated ability to implement and adapt research papers into working code, excellent problem-solving skills, and strong communication skills are also necessary. Preferred qualifications include a research focus during your PhD in areas relevant to our work (NLP, computer vision, multimodal learning), familiarity with distributed training systems for large-scale models, experience with model quantization, pruning, and other efficiency techniques, understanding of evaluation methodologies for assessing model performance, knowledge of MLOps practices and tools for model deployment, and publications at top-tier ML conferences (NeurIPS, ICML, ACL, CVPR, etc.). In return, we offer an ideal transition from academic research to industry application, a structured onboarding program designed specifically for recent PhD graduates, the opportunity to work on frontier AI models with real-world impact, access to significant computing resources for ambitious research, a collaborative environment with other top AI researchers and engineers, flexible work arrangements, competitive compensation, support for continued professional development and conference attendance, and a clear path for growth into senior technical or leadership roles. FourKites is the leader in AI-driven supply chain transformation for global enterprises, pioneering real-time visibility and turning supply chain data into automated action. Our Intelligent Control Tower breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory, and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across the supply chain. In addition to the exciting work environment, we offer medical benefits starting on the first day of employment, 36 PTO days (sick, casual, and earned), 5 recharge days, 2 volunteer days, home office setups, and technology reimbursement, lifestyle and family benefits, annual swags/festive swags, ongoing learning and development opportunities (professional development program, Toast Master club, etc.).,

Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to Customers. As an AI Engineer with Python at Artmac Soft, you will be responsible for leveraging your 1 year of experience in AI engineering, with a focus on Python programming. Your role will involve utilizing your knowledge of Cursor AI, Render, and CloudFlare, along with proficiency in Python libraries and frameworks like TensorFlow, PyTorch, sci-kit-learn, NumPy, and pandas. You will need a strong understanding of machine learning algorithms and deep learning architectures to develop AI/ML models that address business challenges. In this role, you will collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate AI solutions into products. Your responsibilities will also include building and maintaining scalable data pipelines for machine learning workflows, optimizing AI models for performance and accuracy, and developing APIs and services to deploy AI models in production environments. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Additionally, you must have experience with cloud platforms like AWS, GCP, or Azure, as well as containerization tools such as Docker and Kubernetes. Knowledge of CI/CD pipelines, MLOps practices, NLP, computer vision, distributed computing, big data technologies, version control systems like Git, real-time data processing, and streaming will be beneficial. You will also be expected to stay updated on the latest advancements in AI, machine learning, and deep learning, while documenting AI solutions, workflows, and best practices. Monitoring, evaluating, and troubleshooting deployed models to ensure reliability and performance will be part of your routine tasks, along with data preprocessing, feature engineering, and exploratory data analysis. If you are passionate about AI, Python programming, and leveraging cutting-edge technologies to drive business outcomes, we encourage you to apply for this Full-Time position based in Hyderabad, Telangana. Join us at Artmac Soft and be part of a team that is dedicated to delivering innovative technology solutions to our customers.,

Neuron7.ai is a rapidly growing AI-first SaaS company that focuses on creating a category-defining service intelligence product. Backed by top venture capitalists in Silicon Valley and a distinguished group of angel advisors/investors, Neuron7.ai is recognized as a startup to watch. Our rapid traction in the market underscores our mission to empower enterprises to make accurate service decisions at scale. Our AI-driven platform delivers service predictions in seconds by analyzing structured and unstructured data alongside insights from leading experts. In complex service environments such as high-tech devices, manufacturing, and medical devices, Neuron7.ai helps service leaders excel in critical metrics like first-call resolution, turnaround time, and service margins. Learn more at Neuron7.ai. At Neuron7.ai, you'll be part of a dynamic and innovative team that is redefining service intelligence. We value creativity, collaboration, and a commitment to pushing boundaries. As a Staff Data Scientist at Neuron7.ai, you will lead the design, development, and deployment of NLP-driven solutions for processing and analyzing large volumes of unstructured data. You will bring a deep technical skill set and a passion for innovation to launch impactful AI products to live users. In addition, you will serve as a mentor to junior team members and collaborate closely with cross-functional teams and customers. Lead the development and deployment of NLP-based solutions to process and analyze unstructured data at scale. Design, train, and optimize machine learning models using libraries such as PyTorch, NLTK, and Scikit-learn. Architect and deploy AI/ML products on cloud platforms like Azure, GCP, or AWS. Collaborate with data engineering teams to ensure seamless integration of AI models into production systems. Perform advanced SQL analytics to extract actionable insights from structured datasets. Stay up-to-date with the latest advancements in NLP and machine learning techniques. Mentor junior data scientists and foster a culture of technical excellence within the team. Communicate complex technical concepts to non-technical stakeholders and customers. Partner with customers to understand their needs and translate them into technical solutions. Minimum 8 years of experience in data science, with a focus on NLP and unstructured data processing. Proven track record of launching NLP-driven products to live users. Expertise in Python and standard libraries such as PyTorch, NLTK, and Scikit-learn. Experience with Transformer-based models (e.g., BERT, GPT). Strong experience with one or more cloud platforms (Azure, GCP, AWS) for hosting and deploying AI/ML products. Familiarity with data engineering pipelines and best practices. Proficiency in SQL for analytics and data manipulation. Excellent problem-solving skills and ability to work with large-scale datasets. Strong interpersonal and communication skills, with the ability to mentor team members and interact with customers effectively. Preferred Skills: Knowledge of MLOps practices for model deployment and monitoring. Familiarity with tools like Airflow, Spark, or similar data processing frameworks. Background in working with customer-facing applications and APIs. At Neuron7.ai, we prioritize integrity, innovation, and a customer-centric approach. Our mission is to enhance service decision-making through advanced AI technology, and we are dedicated to delivering excellence in all aspects of our work. Company Perks & Benefits: Competitive salary, equity, and spot bonuses. Paid sick leave. Latest MacBook Pro for your work. Comprehensive health insurance. Paid parental leave. Work from our vibrant Bengaluru office. If you're excited about building innovative backend solutions and want to be part of a forward-thinking team, we'd love to hear from you!,

You are looking for talented and innovative AI/ML Specialists to join your team. The ideal candidate will have experience in designing, developing, and deploying machine learning models, working with large datasets, and optimizing AI-driven solutions for various applications. If you are passionate about AI and machine learning and want to work on cutting-edge technology, we encourage you to apply. Responsibilities: - Design, develop, and deploy AI and machine learning models for real-world applications. - Train, test, troubleshoot and fine-tune machine learning models to enhance accuracy and performance. - Work with large-scale datasets to extract meaningful insights and improve model efficiency. - Develop and integrate AI/ML algorithms into production systems. - Optimize models for scalability, efficiency, and real-time performance by staying updated with industry new trends & technologies. - Implement and maintain MLOps practices for continuous integration and deployment of AI models. Requirements: - Bachelors or Masters degree in Computer Science and Engineering. - Proven expertise in AI/ML development and deployment. - Proficiency in programming languages (Python, R, Java). - Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. - Strong understanding of deep learning, natural language processing (NLP), and computer vision. - Knowledge of cloud computing platforms such as AWS, Google Cloud, or Azure. - Experience with big data technologies like Hadoop or Spark is desirable. - Familiarity with model versioning, model monitoring, and MLOps best practices. - Strong problem-solving and analytical skills. Preferred Qualifications: - Experience with AI model deployment in cloud environments. - Contributions to open-source AI projects or published research in AI/ML. If you are excited about AI and machine learning technology and want to make an impact, the team would love to hear from you!,

We are a technology-led healthcare solutions provider with a purpose to enable healthcare organizations to be future-ready. We offer accelerated global growth opportunities for individuals who are bold, industrious, and nimble. At Indegene, you will experience a unique career journey that celebrates entrepreneurship and is guided by passion, innovation, collaboration, and empathy. If you are interested in exploring exciting opportunities at the convergence of healthcare and technology, visit www.careers.indegene.com. If you are seeking an exciting role in an entrepreneurial organization without the usual risks associated with it, then this opportunity is for you. We understand your desire for growth and variety in your career and invite you to join us in our journey of growth. At Indegene, our roles offer the excitement you seek at this stage of your career along with the reliability you desire. We hire the best talent and trust them to make a global impact from day one, handle teams, and take responsibility for outcomes while being supported and mentored by our leaders. As a profitable and rapidly growing global organization, we are currently seeking top talent to join us in this phase of growth. Working with us will place you at the intersection of two dynamic industries - healthcare and technology. You will have access to global opportunities for fast-track careers while collaborating with a purpose-driven team. This unique combination promises a truly differentiated experience for you. Role: Senior Analyst - Data Science We are in search of a results-driven and hands-on Lead Data Scientist/Analyst with 5-6 years of experience to lead analytical solutioning and model development in the pharmaceutical commercial analytics domain. The ideal candidate will play a pivotal role in designing and deploying Decision Engine frameworks, implementing advanced analytics solutions, and mentoring junior team members. Key Responsibilities: - Collaborate with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. - Design and implement Decision Engine workflows to support Next Best Action (NBA) recommendations in omnichannel engagement strategies. - Analyze large and complex datasets from sources like APLD, sales, CRM, call plans, market share, patient claims, and segmentation data. - Conduct ad hoc and deep-dive analyses to address critical business questions across commercial and medical teams. - Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. - Implement MLOps pipelines using Dataiku, Git, and AWS services to support scalable and repeatable deployment of analytics models. - Ensure data quality through systematic QC checks, test case creation, and validation frameworks. - Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, model interpretability, and cloud-based workflows. - Stay updated with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. Must Have: - 5 years of hands-on experience in pharmaceutical commercial analytics, including exposure to cross-functional brand analytics, omnichannel measurement, and ML modeling. - Minimum of 3 years of experience in developing and deploying predictive models and ML pipelines in real-world settings. - Proficiency in data platforms such as Snowflake, Dataiku, AWS, and expertise in PySpark, Python, and SQL. - Experience with MLOps practices, including version control, model monitoring, and automation. - Strong understanding of pharmaceutical data assets (e.g., APLD, DDD, NBRx, TRx, specialty pharmacy, CRM, digital engagement). - Proficiency in ML algorithms (e.g., XGBoost, Random Forest, SVM, Logistic Regression, Neural Networks, NLP). - Expertise in key use cases: Next Best Action, Recommendation Engines, Attribution Models, Segmentation, Marketing ROI, Collaborative Filtering. - Hands-on experience in building explainable ML models and using tools for model monitoring and retraining. - Familiarity with dashboarding tools like Tableau or PowerBI is a plus. - Excellent communication and documentation skills to effectively convey findings to both technical and non-technical audiences. - Ability to work in a dynamic, fast-paced environment and deliver results under tight timelines. EQUAL OPPORTUNITY Location: Bangalore, KA, IN If this opportunity excites you, please apply below.,

Neuron7.ai is a rapidly growing AI-first SaaS company focused on creating a category-defining service intelligence product. Backed by top venture capitalists in Silicon Valley and a distinguished group of angel advisors/investors, Neuron7.ai is recognized as a startup to watch. The company's swift traction in the market underscores its mission to empower enterprises to make accurate service decisions at scale. The AI-driven platform delivers service predictions in seconds by analyzing structured and unstructured data alongside insights from leading experts. In complex service environments such as high-tech devices, manufacturing, and medical devices, Neuron7.ai helps service leaders excel in critical metrics like first-call resolution, turnaround time, and service margins. At Neuron7.ai, you will be part of a dynamic and innovative team that is redefining service intelligence. The company values creativity, collaboration, and a commitment to pushing boundaries. As a Staff Data Scientist at Neuron7.ai, you will lead the design, development, and deployment of NLP-driven solutions for processing and analyzing large volumes of unstructured data. Your role will involve designing, training, and optimizing machine learning models using libraries such as PyTorch, NLTK, and Scikit-learn. You will also architect and deploy AI/ML products on cloud platforms like Azure, GCP, or AWS, collaborating closely with data engineering teams to ensure seamless integration of AI models into production systems. Additionally, you will perform advanced SQL analytics to extract actionable insights from structured datasets and stay up-to-date with the latest advancements in NLP and machine learning techniques. Mentoring junior data scientists, fostering a culture of technical excellence within the team, and effectively communicating complex technical concepts to non-technical stakeholders and customers are also key aspects of the role. Neuron7.ai is looking for a candidate with a minimum of 12 years of experience in data science, with a focus on NLP, LLM, and unstructured data processing. The ideal candidate should have a proven track record of launching NLP-driven products to live users, expertise in Python and standard libraries such as PyTorch, NLTK, and Scikit-learn, and experience with Transformer-based models (e.g., BERT, RAG, GPT, Gen AI), among other requirements. Strong interpersonal and communication skills, proficiency in SQL for analytics and data manipulation, and the ability to work with large-scale datasets are also essential qualifications. Preferred skills for the role include knowledge of MLOps practices for model deployment and monitoring, familiarity with tools like Airflow, Spark, or similar data processing frameworks, and a background in working with customer-facing applications and APIs. At Neuron7.ai, integrity, innovation, and a customer-centric approach are prioritized values. The company's mission is to enhance service decision-making through advanced AI technology, delivering excellence in all aspects of its work. Company perks and benefits at Neuron7.ai include a competitive salary, equity, and spot bonuses, paid sick leave, a latest MacBook Pro for work, comprehensive health insurance, paid parental leave, and the opportunity to work from the vibrant Bengaluru office in a hybrid model. If you are excited about building innovative backend solutions and want to be part of a forward-thinking team, Neuron7.ai would love to hear from you.,

As a Gen AI Support Specialist at Boston Scientific, you will have the opportunity to work in a team of diverse and high-performing individuals to tackle significant challenges in the health industry. You will be responsible for assisting teams with AI-based solutions, ensuring optimal performance of AI models, and supporting the deployment of AI applications in cloud environments. Your role will involve collaborating with data scientists and engineers to fine-tune models, developing and maintaining Python scripts, deploying AI solutions in AWS cloud environments, and designing interactive applications using Streamlit. Key Responsibilities - Assist in the deployment, integration, and maintenance of Generative AI models. - Troubleshoot and resolve issues related to AI model performance and deployment. - Collaborate with data scientists and engineers to fine-tune models for specific use cases. - Develop and maintain Python scripts for data preprocessing, model training, and evaluation. - Deploy and manage AI solutions in AWS cloud environments. - Design and build user-friendly dashboards and interactive applications using Streamlit. - Work closely with cross-functional teams to document workflows, processes, and technical details. - Provide training and support to stakeholders on AI tools and applications. Your Experience Technical Expertise: - Proficient in Python programming with knowledge of libraries such as NumPy, Pandas, and PyTorch/TensorFlow. - Hands-on experience with AWS services for AI/ML applications. - Expertise in developing applications using Streamlit. AI Knowledge: - Familiarity with Generative AI concepts and frameworks. - Experience in model deployment, monitoring, and optimization. Soft Skills: - Strong problem-solving abilities and analytical thinking. - Excellent communication skills for conveying complex ideas clearly. - Proven ability to work in a collaborative team environment. Preferred Qualifications: - Certifications in AWS, such as AWS Certified Machine Learning - Specialty. - Prior experience with MLOps practices and tools. - Knowledge of front-end frameworks and UI/UX principles for Streamlit enhancements. Join Boston Scientific in its mission to advance science for life and make a meaningful difference in the world. Apply now to be part of a global business committed to improving patient lives and supporting employees and communities worldwide.,

You are a highly skilled GenAI Lead Engineer responsible for designing and implementing advanced frameworks for alternate data analysis in the investment management domain. You will leverage LLM APIs (GPT, LLaMA, etc.), build scalable orchestration pipelines, and architect cloud/private deployments to drive next-generation AI-driven investment insights. Your role includes leading a cross-functional team of Machine Learning Engineers and UI Developers to deliver robust, production-ready solutions. Your responsibilities will include developing custom frameworks using GPT APIs or LLaMA for alternate data analysis and insights generation. You will optimize LLM usage for investment-specific workflows, including data enrichment, summarization, and predictive analysis. Additionally, you will design and implement document ingestion workflows using tools such as n8n (or similar orchestration frameworks) and build modular pipelines for structured and unstructured data. You are also expected to architect deployment strategies on cloud (AWS, GCP, Azure) or private compute environments (CoreWeave, on-premises GPU clusters) ensuring high availability, scalability, and security in deployed AI systems. The ideal candidate should have a strong proficiency in Python with experience in frameworks such as TensorFlow or PyTorch. You must have 2+ years of experience in Generative AI and Large Language Models (LLMs) along with experience with VectorDBs (e.g., Pinecone, Weaviate, Milvus, FAISS) and document ingestion pipelines. Familiarity with data orchestration tools (e.g., n8n, Airflow, LangChain Agents), cloud deployments, GPU infrastructure (CoreWeave or equivalent), proven leadership skills, and experience managing cross-functional engineering teams are essential. Strong problem-solving skills, the ability to work in fast-paced, data-driven environments, experience with financial or investment data platforms, knowledge of RAG (Retrieval-Augmented Generation) systems, familiarity with frontend integration for AI-powered applications, and exposure to MLOps practices for continuous training and deployment are also required.,

We are seeking an experienced and customer-centric Cloud Solutions Architect to fulfill a dual role encompassing presales solutioning and delivery execution. This position necessitates alignment with US business hours (2pm10pm IST) and entails close collaboration with North American clients. The ideal candidate should possess extensive expertise in AWS cloud services, modern data platforms, and AI/ML workloads, along with a robust ability to translate intricate technical requirements into scalable, secure, and cost-effective solutions. Moreover, familiarity with Azure and Google Cloud Platform (GCP) would be advantageous. In the realm of Presales & Solution Engineering, your responsibilities will involve direct engagement with US-based enterprise customers to grasp their business objectives, technical prerequisites, and pain points. You will be tasked with designing and recommending cloud-native solutions on AWS encompassing compute, storage, networking, security, and DevOps. Crafting impactful solution blueprints, technical proposals, and reference architectures, as well as leading and supporting RFP/RFI responses, customer demos, and technical workshops will be integral aspects of your role. Additionally, collaborating with Sales, Product, and Delivery teams to align technical solutions with business objectives and conducting Proof-of-Concepts (PoCs) to validate solutions are key responsibilities. Transitioning to Delivery & Execution, you will be responsible for ensuring a seamless handover and alignment between presales and delivery, providing technical leadership across the project lifecycle including architecture reviews, implementation guidance, troubleshooting, and optimization. Engaging with client stakeholders, technical teams, and project managers during delivery phases, advocating best practices for cloud adoption, performance tuning, cost optimization, and security compliance, and assisting internal delivery teams in resolving complex architecture challenges are pivotal elements of this role. In terms of Technical Expertise, you should possess comprehensive knowledge in AWS Cloud Architecture encompassing IaaS (e.g., EC2, VPC, S3, EBS, ELB, Auto Scaling), PaaS (e.g., RDS, Lambda, API Gateway, DynamoDB, Aurora, Fargate, Step Functions) and Security & SaaS (e.g., IAM, AWS Organizations, WAF, GuardDuty, CloudTrail). Furthermore, familiarity with Multi-Cloud environments such as Azure (e.g., Synapse, Azure ML, AKS) and GCP (e.g., BigQuery, Vertex AI, GKE), DevOps & Automation tools (e.g., Terraform, CloudFormation, Jenkins, GitOps, CI/CD pipelines), and Data Platforms & AI/ML technologies is essential. The role necessitates a Bachelor's/Masters degree in Computer Science, Information Technology, or a related discipline, with a minimum of 10 years in IT, including at least 5 years in cloud architecture and presales/delivery roles. Possession of an AWS Certified Solutions Architect - Professional certification is preferred. Strong communication and stakeholder management skills are crucial, as is the ability to present to CXOs, architects, and engineering teams. Experience in bridging presales engagements with hands-on technical delivery is a key requirement. Additionally, domain expertise in verticals like finance, healthcare, or retail cloud transformation, familiarity with container orchestration (EKS, AKS, GKE), and MLOps platforms (Kubeflow, etc.) would be advantageous. The position entails working hours from 2:00 PM to 10:00 PM IST to cater to US-based clients and is based in Hyderabad.,

Onelab Ventures is a leading technology company specializing in custom AI agent solutions and software development. We transform ideas into innovative products and intelligent systems, driving growth and efficiency for startups and enterprises. Our experienced team collaborates closely with clients, delivering functional and scalable solutions. With over 100 successful projects and users across various industries, including AI, SaaS, Fintech, and Healthcare, we combine state-of-the-art technologies and advanced AI frameworks to create products that optimize operations and disrupt industries. This is a full-time, on-site role for an IT Project Manager specializing in AI/ML, located in Pune. The IT Project Manager will be responsible for overseeing the planning, execution, and delivery of AI and machine learning projects. The ideal candidate has a strong understanding of artificial intelligence technologies, software development life cycle (SDLC), and experience working closely with cross-functional teams including data scientists, engineers, and business stakeholders. You will be responsible for managing timelines, resources, and risks to ensure successful deployment of AI-powered solutions that drive business value. Key Responsibilities: - Lead end-to-end project management for AI/ML and data science initiatives, from project scoping to delivery. - Collaborate with product owners, data scientists, ML engineers, and developers to define project goals and technical requirements. - Develop and manage detailed project plans, schedules, and resource allocation. - Ensure alignment between AI models and business objectives through regular stakeholder communication. - Track project milestones and performance against goals using tools like Jira, Trello, or Asana. - Identify project risks, roadblocks, and dependencies; implement mitigation strategies. - Oversee model development, testing, integration, and deployment with software teams. - Ensure compliance with ethical AI standards, data privacy regulations, and security protocols. - Drive continuous improvement in project delivery and AI solutions. Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field. - 5+ years of experience in project management, preferably in AI/ML or data-driven environments. - Solid understanding of AI/ML workflows, tools, and deployment lifecycles. - Familiarity with Python, cloud platforms (AWS/GCP/Azure), and ML frameworks is a plus. - Strong knowledge of Agile/Scrum methodologies and SDLC practices. - Excellent organizational, analytical, and communication skills. - Proven ability to manage multiple complex projects and meet tight deadlines. - PMP, PMI-ACP, or Scrum Master certification. - Experience with MLOps practices and model lifecycle management. - Prior experience working with AI products such as chatbots, recommendation engines, or NLP-based applications. - Ability to bridge the gap between technical teams and business stakeholders. This role at Onelab Ventures offers an exciting opportunity to lead cutting-edge AI projects and contribute to the success of innovative solutions in a dynamic and collaborative environment.,