1795 Mlflow Jobs - Page 8

ROLES & RESPONSIBILITIES Qualifications and Skills: •Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field. 5+ years of hands-on experience in data science or machine learning roles. Strong proficiency in Python or R, with deep knowledge of libraries like scikit-learn, pandas, NumPy, TensorFlow, or PyTorch. Proficient in SQL and working with relational databases. Solid experience with Azure cloud platforms and data pipeline tools. Strong grasp of statistical methods, machine learning algorithms, and model evaluation techniques. Excellent communication and storytelling skills with the ability to influence stakeholders. Proven track record of delivering impactful data science solutions in a business setting. Preferred Qualifications: Experience working in industries such as [logistics, aerospace, marketing, etc.]. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Knowledge of data visualization tools (e.g., Tableau, Power BI, Plotly). Responsibilities and Duties Model Development: Design, build, and deploy scalable machine learning models to solve key business challenges (e.g., customer churn, recommendation engines, pricing optimization). Data Analysis: Perform exploratory data analysis (EDA), statistical testing, and feature engineering to uncover trends and actionable insights. Project Leadership: Lead end-to-end data science projects, including problem definition, data acquisition, modeling, and presentation of results to stakeholders. Cross-functional Collaboration: Partner with engineering, product, marketing, and business teams to integrate models into products and processes. Mentorship: Guide and mentor junior data scientists and analysts, helping them grow technically and professionally. Innovation: Stay current with the latest data science techniques, tools, and best practices. Evaluate and incorporate new technologies when appropriate. Communication: Translate complex analyses and findings into clear, compelling narratives for non-technical stakeholders. EXPERIENCE 8-11 Years SKILLS Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): Data Science ABOUT THE COMPANY Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP). Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.

Location Gurugram, Jaipur Employment Type Full time Location Type Hybrid Department Engineering For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram. Position Description: We are seeking a Machine Learning Engineer to join our growing AI team at PAR . This role will focus on developing and scaling GenAI-powered services, recommender systems, and ML infrastructure that fuel personalized customer engagement. You will work across teams to drive technical excellence and real-world ML application impact. Position Location: Jaipur / Gurgaon Reports To: [Hiring Manager Title – e.g., Head of AI or Senior Director, AI Engineering] What We’re Looking For: Entrees (Requirements): Master’s or PhD in Computer Science, Machine Learning, or a related field 3+ years of experience delivering production-ready machine learning solutions Deep understanding of ML algorithms , recommender systems , and NLP Experience with LLM frameworks (Hugging Face Transformers, LangChain, OpenAI API, Cohere) Strong proficiency in Python , including object-oriented design and scalable architecture Advanced expertise in Databricks : notebooks, MLflow tracking, data pipelines, job orchestration Hands-on experience with cloud-native technologies – preferably AWS (S3, Lambda, ECS/EKS, SageMaker) Experience working with modern data platforms : Delta Lake, Redis, Elasticsearch, NoSQL, BigQuery Strong verbal and written communication skills to translate technical work into business impact Flexibility to collaborate with global teams in PST/EST time zones when required With a Side of (Additional Skills): Familiarity with vector databases (FAISS, ChromaDB, Pinecone, Weaviate) Experience with retrieval-augmented generation (RAG) and hybrid search systems Skilled in deploying ML APIs using FastAPI or Flask Background in text-to-SQL applications or domain-specific LLMs Knowledge of ML Ops practices: model versioning, automated retraining, monitoring Familiarity with CI/CD for ML pipelines via Databricks Repos, GitHub Actions, etc. Contributions to open-source ML or GenAI projects Experience in the restaurant/hospitality tech or digital marketing domain Unleash Your Potential: What You Will Be Doing and Owning: Build and deploy GenAI-powered microservices and personalized recommendation engines Design and manage Databricks data pipelines for training, feature engineering, and inference Develop high-performance ML APIs and integrate with frontend applications Implement retrieval pipelines with vector DBs and search engines Define and maintain ML Ops workflows for versioning, retraining, and monitoring Drive strategic architectural decisions for LLM-powered, multi-model systems Collaborate across product and engineering teams to embed intelligence in customer experiences Enable CI/CD for ML systems with modern orchestration tools Advocate for scalability, performance, and clean code in all deployed solutions Interview Process: Interview #1: Phone Screen with Talent Acquisition Team Interview #2: Technical Interview – Round 1 with AI/ML Team (via MS Teams / F2F) Interview #3: Technical Interview – Round 2 with AI/ML Team (via MS Teams / F2F) Interview #4: Final Round with Hiring Manager and Cross-functional Stakeholders (via MS Teams / F2F PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.

For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram. Position Description We are seeking a Machine Learning Engineer to join our growing AI team at PAR . This role will focus on developing and scaling GenAI-powered services, recommender systems, and ML infrastructure that fuel personalized customer engagement. You will work across teams to drive technical excellence and real-world ML application impact. Position Location: Jaipur / Gurgaon Reports To [Hiring Manager Title – e.g., Head of AI or Senior Director, AI Engineering] Entrees (Requirements) What We’re Looking For: Master’s or PhD in Computer Science, Machine Learning, or a related field 3+ years of experience delivering production-ready machine learning solutions Deep understanding of ML algorithms, recommender systems, and NLP Experience with LLM frameworks (Hugging Face Transformers, LangChain, OpenAI API, Cohere) Strong proficiency in Python, including object-oriented design and scalable architecture Advanced expertise in Databricks: notebooks, MLflow tracking, data pipelines, job orchestration Hands-on experience with cloud-native technologies – preferably AWS (S3, Lambda, ECS/EKS, SageMaker) Experience working with modern data platforms: Delta Lake, Redis, Elasticsearch, NoSQL, BigQuery Strong verbal and written communication skills to translate technical work into business impact Flexibility to collaborate with global teams in PST/EST time zones when required With a Side Of (Additional Skills) Familiarity with vector databases (FAISS, ChromaDB, Pinecone, Weaviate) Experience with retrieval-augmented generation (RAG) and hybrid search systems Skilled in deploying ML APIs using FastAPI or Flask Background in text-to-SQL applications or domain-specific LLMs Knowledge of ML Ops practices: model versioning, automated retraining, monitoring Familiarity with CI/CD for ML pipelines via Databricks Repos, GitHub Actions, etc. Contributions to open-source ML or GenAI projects Experience in the restaurant/hospitality tech or digital marketing domain Unleash Your Potential: What You Will Be Doing and Owning: Build and deploy GenAI-powered microservices and personalized recommendation engines Design and manage Databricks data pipelines for training, feature engineering, and inference Develop high-performance ML APIs and integrate with frontend applications Implement retrieval pipelines with vector DBs and search engines Define and maintain ML Ops workflows for versioning, retraining, and monitoring Drive strategic architectural decisions for LLM-powered, multi-model systems Collaborate across product and engineering teams to embed intelligence in customer experiences Enable CI/CD for ML systems with modern orchestration tools Advocate for scalability, performance, and clean code in all deployed solutions Interview Process Interview #1: Phone Screen with Talent Acquisition Team Interview #2: Technical Interview – Round 1 with AI/ML Team (via MS Teams / F2F) Interview #3: Technical Interview – Round 2 with AI/ML Team (via MS Teams / F2F) Interview #4: Final Round with Hiring Manager and Cross-functional Stakeholders (via MS Teams / F2F PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.

We are seeking a visionary AI Architect to lead the design and integration of cutting-edge AI systems, including Generative AI , Large Language Models (LLMs) , multi-agent orchestration , and retrieval-augmented generation (RAG) frameworks. This role demands a strong technical foundation in machine learning, deep learning, and AI infrastructure, along with hands-on experience in building scalable, production-grade AI systems on the cloud. The ideal candidate combines architectural leadership with hands-on proficiency in modern AI frameworks, and can translate complex business goals into innovative, AI-driven technical solutions. Primary Stack & Tools: Languages : Python, SQL, Bash ML/AI Frameworks : PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers GenAI & LLM Tooling : OpenAI APIs, LangChain, LlamaIndex, Cohere, Claude, Azure OpenAI Agentic & Multi-Agent Frameworks : LangGraph, CrewAI, Agno, AutoGen Search & Retrieval : FAISS, Pinecone, Weaviate, Elasticsearch Cloud Platforms : AWS, GCP, Azure (preferred: Vertex AI, SageMaker, Bedrock) MLOps & DevOps : MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines, Terraform, FAST API Data Tools : Snowflake, BigQuery, Spark, Airflow Key Responsibilities: Architect scalable and secure AI systems leveraging LLMs , GenAI , and multi-agent frameworks to support diverse enterprise use cases (e.g., automation, personalization, intelligent search). Design and oversee implementation of retrieval-augmented generation (RAG) pipelines integrating vector databases, LLMs, and proprietary knowledge bases. Build robust agentic workflows using tools like LangGraph , CrewAI , or Agno , enabling autonomous task execution, planning, memory, and tool use. Collaborate with product, engineering, and data teams to translate business requirements into architectural blueprints and technical roadmaps. Define and enforce AI/ML infrastructure best practices , including security, scalability, observability, and model governance. Manage technical road-map, sprint cadence, and 3–5 AI engineers; coach on best practices. Lead AI solution design reviews and ensure alignment with compliance, ethics, and responsible AI standards. Evaluate emerging GenAI & agentic tools; run proofs-of-concept and guide build-vs-buy decisions. Qualifications: 10+ years of experience in AI/ML engineering or data science, with 3+ years in AI architecture or system design. Proven experience designing and deploying LLM-based solutions at scale, including fine-tuning , prompt engineering , and RAG-based systems . Strong understanding of agentic AI design principles , multi-agent orchestration , and tool-augmented LLMs . Proficiency with cloud-native ML/AI services and infrastructure design across AWS, GCP, or Azure. Deep expertise in model lifecycle management, MLOps, and deployment workflows (batch, real-time, streaming). Familiarity with data governance , AI ethics , and security considerations in production-grade systems. Excellent communication and leadership skills, with the ability to influence technical and business stakeholders.

SLSQ126R545 As an Enterprise Account Executive at Databricks, you are a sales professional experienced in leading go-to-market campaigns in one of the largest Banking institutions in India. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in depth and are passionate about communicating value to Customers and System Integrators. Databricks operates at the leading edge of the Unified Data Analytics and AI space. Our customers turn to us to lead the accelerated innovation that their businesses need to gain a first mover advantage in today’s ultra-competitive landscape. As we continue our rapid expansion, we are looking for a creative, execution-oriented Enterprise Account Executive to join the Retail & CPG team and maximize the phenomenal market opportunity that exists for Databricks. Reporting to our Director of Enterprise Sales, you will manage a strategic enterprise client in the BFSI vertical. Your informed perspective on Big Data, Advanced Analytics, and AI will help guide your successful execution strategy and allow you to provide genuine value to the client. The Impact You Will Have Present a territory plan within the first 90 days Meet with CIOs, IT executives, LOB executives, Program Managers, and other important partners Close both new accounts and existing accounts Identify and close quick, small wins while managing longer, complex sales cycles Exceed activity, pipeline, and revenue targets Track all customer details, including use case, purchase time frames, next steps, and forecasting in Salesforce Use a solution-based approach to selling and creating value for customers Promote Databricks' enterprise cloud data platform powered by Apache Spark Ensure 100% satisfaction among all customers Prioritize opportunities and apply appropriate resources Build a plan for success internally at Databricks and externally with your accounts What We Look For Previous field sales experience within big data, Cloud, SaaS, and a consumption selling motion Prior customer relationships with CIOs, program managers, and essential decision makers at local accounts The ability to simplify a technical capability into a value-based benefit 7+ years of Enterprise Sales experience exceeding quotas in BFSI accounts like ICICI Bachelor's Degree About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

SLSQ126R458 As an Enterprise Account Executive at Databricks, you are a sales professional experienced in leading go-to-market campaigns in a few of the largest Indian conglomerates. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in depth and are passionate about communicating value to Customers and System Integrators. Databricks operates at the cutting edge of the Unified Data Analytics and AI space. Our customers turn to us to lead the accelerated innovation that their businesses need to gain a first-mover advantage in today’s ultra-competitive landscape. As we continue our rapid expansion, we are looking for a creative, execution-oriented Enterprise Account Executive to join us and maximize the phenomenal market opportunity that exists for Databricks. Reporting to our Director of Enterprise Sales, you will manage a strategic enterprise vertical. Your informed perspective on Big Data, Advanced Analytics, and AI will help guide your successful execution strategy and allow you to provide genuine value to the client. The Impact You Will Have Present a territory plan within the first 90 days Meet with CIOs, IT executives, LOB executives, Program Managers, and other important partners Close both new accounts and existing accounts Identify and close quick, small wins while managing longer, complex sales cycles Exceed activity, pipeline, and revenue targets Track all customer details, including use case, purchase time frames, next steps, and forecasting in Salesforce Use a solution-based approach to selling and creating value for customers Promote Databricks' enterprise cloud data platform powered by Apache Spark Ensure 100% satisfaction among all customers Prioritize opportunities and apply appropriate resources Build a plan for success internally at Databricks and externally with your accounts. What We Look For Previous field sales experience within big data, Cloud, SaaS, and a consumption selling motion Prior customer relationships with CIOs, program managers, and essential decision makers at local accounts The ability to simplify a technical capability into a value-based benefit 7+ years of Enterprise Sales experience exceeding quotas in larger accounts (preferably with Indian conglomerate like Reliance.) Managing a small set of enterprise accounts rather than a broad territory Bachelor's Degree About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

computer vision or deep learning roles industrial/safety inspection datasets (e.g., PPE detection, visual defect classification). Familiarity with MLOps tools like MLflow, DVC, or ClearML. ONNX, TensorRT, OpenVINO

Hi, Please check the below role and let me know if you are interested. Share me your updated resume Position: Data Engineer Work Location: Kochi, Coimbatore, Chennai Work Type: Hybrid Onsite, 3 days onsite every week Experience-3+ Skills & Responsibilities: Data Engineering & Processing: Develop scalable data pipelines using Python and PySpark in Azure Databricks Work on data ingestion, cleansing, transformation, and preparation for analytics. Databricks & Azure Platform Skills: Hands-on experience with Databricks notebooks, Delta Lake, and working with structured and semi- structured data; MLFlow, use Azure Data Factory, Azure Data Lake, Azure SQL, and Cosmos DB for data processing and storage. Programming Skills: Strong proficiency in Python for data manipulation, automation, and orchestration tasks; familiarity with PySpark for distributed processing of large datasets. CI/CD & DevOps: Use Azure DevOps for version control, automated testing, and pipeline-based deployments; follow coding standards and peer review processes. Testing & Quality: Write and execute unit and validation tests for data pipelines; monitor job performance and troubleshoot data quality issues. Agile Collaboration: Participate in Agile ceremonies including stand-ups, sprint planning, and retrospectives; work closely with BAs, QAs, and architects to deliver high-quality solutions. Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Job Type: Contractual / Temporary Contract length: 12 months Pay: ₹800,000.00 - ₹1,800,000.00 per year Schedule: Day shift Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Location: Chennai, Tamil Nadu (Required) Work Location: In person

Company Description About Sutherland Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise. We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence. We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model. For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland Unlocking digital performance. Delivering measurable results. Job Description We are looking for a proactive and detail-oriented AI OPS Engineer to support the deployment, monitoring, and maintenance of AI/ML models in production. Reporting to the AI Developer, this role will focus on MLOps practices including model versioning, CI/CD, observability, and performance optimization in cloud and hybrid environments. Key Responsibilities: Build and manage CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker. Monitor model performance and health using observability tools and dashboards. Ensure automated retraining, version control, rollback strategies, and audit logging for production models. Support deployment of LLMs, RAG pipelines, and agentic AI systems in scalable, containerized environments. Collaborate with AI Developers and Architects to ensure reliable and secure integration of models into enterprise systems. Troubleshoot runtime issues, latency, and accuracy drift in model predictions and APIs. Contribute to infrastructure automation using Terraform, Docker, Kubernetes, or similar technologies. Qualifications Required Qualifications: 3–5 years of experience in DevOps, MLOps, or platform engineering roles with exposure to AI/ML workflows. Hands-on experience with deployment tools like Jenkins, Argo, GitHub Actions, or Azure DevOps. Strong scripting skills (Python, Bash) and familiarity with cloud environments (AWS, Azure, GCP). Understanding of containerization, service orchestration, and monitoring tools (Prometheus, Grafana, ELK). Bachelor’s degree in computer science, IT, or a related field. Preferred Skills: Experience supporting GenAI or LLM applications in production. Familiarity with vector databases, model registries, and feature stores. Exposure to security and compliance standards in model lifecycle management

Responsibilities and Duties: Strategic Leadership (10%): Champion the AI/ML roadmap, driving strategic planning and execution for all initiatives. Provide guidance on data science projects (Agentic AI, Generative AI, and Machine Learning), aligning them with business objectives and best practices. Foster a data-driven culture, advocating for AI-powered solutions to business challenges and efficiency improvements. Collaborate with product management, engineering, and business stakeholders to identify opportunities and deliver impactful solutions Technical Leadership (40%): Architect and develop Proof-of-Concept (POC) solutions for Agentic AI, Generative AI, and ML. Utilize Python and relevant data science libraries, leveraging MLflow. Provide technical guidance on AI projects, ensuring alignment with business objectives and best practices. Assist in development and documentation of standards for ethical and regulatory-compliant AI usage. Stay current with AI advancements, contributing to the team's knowledge and expertise. Perform hands-on data wrangling and AI model development Operational Leadership (50%): Drive continuous improvement through Agentic AI, Generative AI, and predictive modeling. Participate in Agile development processes (Scrum and Kanban). Ensure compliance with regulatory and ethical AI standards. Other duties as assigned Required Abilities and Skills: Agentic AI development and deployment. Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Working with large datasets on AWS and Databricks Strong hands-on experience with: Agentic AI development and deployment. Working with large datasets on AWS and Databricks. Desired Experience: Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Experience integrating AI with IoT/event data. Experience with real-time and batch inference integration with SaaS applications. International team management experience. Track record of successful product launches in regulated environments Education and Experience: 5+ years of data science/AI experience Bachelor's degree in Statistics, Data Science, Computer Engineering, Mathematics, or a related field (Master's preferred). Proven track record of deploying successful Agentic AI, Generative AI, and ML projects from concept to production. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences.

Roles & Responsibilities Qualifications and Skills: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field. 5+ years of hands-on experience in data science or machine learning roles. Strong proficiency in Python or R, with deep knowledge of libraries like scikit-learn, pandas, NumPy, TensorFlow, or PyTorch. Proficient in SQL and working with relational databases. Solid experience with Azure cloud platforms and data pipeline tools. Strong grasp of statistical methods, machine learning algorithms, and model evaluation techniques. Excellent communication and storytelling skills with the ability to influence stakeholders. Proven track record of delivering impactful data science solutions in a business setting. Preferred Qualifications Experience working in industries such as [logistics, aerospace, marketing, etc.]. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Knowledge of data visualization tools (e.g., Tableau, Power BI, Plotly). Responsibilities And Duties Model Development: Design, build, and deploy scalable machine learning models to solve key business challenges (e.g., customer churn, recommendation engines, pricing optimization). Data Analysis: Perform exploratory data analysis (EDA), statistical testing, and feature engineering to uncover trends and actionable insights. Project Leadership: Lead end-to-end data science projects, including problem definition, data acquisition, modeling, and presentation of results to stakeholders. Cross-functional Collaboration: Partner with engineering, product, marketing, and business teams to integrate models into products and processes. Mentorship: Guide and mentor junior data scientists and analysts, helping them grow technically and professionally. Innovation: Stay current with the latest data science techniques, tools, and best practices. Evaluate and incorporate new technologies when appropriate. Communication: Translate complex analyses and findings into clear, compelling narratives for non-technical stakeholders. Experience 8-11 Years Skills Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): Data Science

Vayuz Technologies is seeking an innovative and self-starting Artificial Intelligence Engineer. You will be an AI expert with a strong background in making architectural tradeoffs to optimize AI performance for a variety of use cases. This role involves close collaboration with internal and external development engineers (architecture, hardware, validation, software services), contributing to development, and supporting device characterization and benchmarking efforts. Responsibilities Large Models & Deep Neural Networks: Demonstrate proficiency and hands-on experience in working with large models and deep neural networks. LLM Expertise: Possess expertise in LLMs with working knowledge of large language models (LLMs). System Architecture: Bring extensive experience in System platform Architecture. Development Experience: Experience in development, preferably for memory/storage/any embedded system. Standards & Patents: Possess in-depth knowledge and extensive experience in dealing with Standardizations, Technical Papers, and Patents. Programming Proficiency: Extensive experience with C/C++ and Python programming. LLM Development & Fine-tuning: Develop and fine-tune LLMs (e.g., GPT, Llama, Mistral, Falcon, Claude) for domain-specific applications. RAG Pipeline Implementation: Implement RAG (Retrieval Augmented Generation) pipelines using tools like LlamaIndex, LangGraph, and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to significantly enhance response accuracy. AI-Powered Agents: Build advanced AI-powered chatbots and autonomous agents using frameworks like LangGraph, CrewAI, and leveraging LlamaIndex and OpenAI APIs. Generative AI Optimization & Deployment: Optimize and deploy generative AI models for real-time inference using cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools (e.g., Docker, Kubernetes, MLflow). Model Fine-tuning Techniques: Fine-tune models using techniques such as LoRA, QLoRA, PEFT, and RLHF to improve efficiency and personalization. AI-Driven Workflows: Develop AI-driven workflows for structured reasoning and decision-making using CrewAI and LangGraph. Multi-Modal AI Integration: Integrate multi-modal AI models (text, image, speech) into comprehensive enterprise solutions. Memory & Retrieval Strategies: Implement memory and retrieval strategies for LLM-based systems using vector search and caching techniques. Ethical AI: Ensure AI models adhere to ethical AI guidelines, incorporate bias mitigation strategies, and follow robust security best practices. Requirements B.Tech in Computer Science or Electrical Engineering. Experience in the relevant domain. Strong analytical and abstract thinking ability, as well as excellent technical communication skills. Able to work independently and perform effectively in a fast-paced environment. Ability to troubleshoot and debug complex issues efficiently. Working knowledge of Device Drivers is desirable. Prior experience in working with Agile/Scrum methodologies. Required Skills Languages & Frameworks: Proficiency in Python, PyTorch, TensorFlow, JAX. LLMs: Large Language Models (GPT, Llama, Mistral, Falcon, Claude). Vector Databases: FAISS, Pinecone, Weaviate, ChromaDB. AI Frameworks: LlamaIndex, LangGraph, CrewAI, OpenAI APIs. MLOps & Cloud: Docker, Kubernetes, MLflow, AWS, GCP, Azure. Fine-tuning: LoRA, QLoRA, PEFT, RLHF.

The role of Data Scientist - Clinical Data Extraction & AI Integration in our healthcare technology team requires an experienced individual with 3-6 years of experience. As a Data Scientist in this role, you will be primarily focused on medical document processing and data extraction systems. You will have the opportunity to work with advanced AI technologies to create solutions that enhance the extraction of crucial information from clinical documents, thereby improving healthcare data workflows and patient care outcomes. Your key responsibilities will include designing and implementing statistical models for medical data quality assessment, developing predictive algorithms for encounter classification, and validation. You will also be responsible for building machine learning pipelines for document pattern recognition, creating data-driven insights from clinical document structures, and implementing feature engineering for medical terminology extraction. Furthermore, you will apply natural language processing (NLP) techniques to clinical text, develop statistical validation frameworks for extracted medical data, and build anomaly detection systems for medical document processing. Additionally, you will create predictive models for discharge date estimation, encounter duration, and implement clustering algorithms for provider and encounter classification. In terms of AI & LLM Integration, you will be expected to integrate and optimize Large Language Models via AWS Bedrock and API services, design and refine AI prompts for clinical content extraction with high accuracy, and implement fallback logic and error handling for AI-powered extraction systems. You will also develop pattern matching algorithms for medical terminology and create validation layers for AI-extracted medical information. Having expertise in the healthcare domain is crucial for this role. You will work closely with medical document structures, implement healthcare-specific validation rules, handle medical terminology extraction, and conduct clinical context analysis. Ensuring HIPAA compliance and adhering to data security best practices will also be part of your responsibilities. Proficiency in programming languages such as Python 3.8+, R, SQL, and JSON, along with familiarity with data science tools like pandas, numpy, scipy, scikit-learn, spaCy, and NLTK is required. Experience with ML Frameworks including TensorFlow, PyTorch, transformers, huggingface, and visualization tools like matplotlib, seaborn, plotly, Tableau, and PowerBI is desirable. Knowledge of AI Platforms such as AWS Bedrock, Anthropic Claude, OpenAI APIs, and experience with cloud services like AWS (SageMaker, S3, Lambda, Bedrock) will be advantageous. Familiarity with research tools like Jupyter notebooks, Git, Docker, and MLflow is also beneficial for this role.,

Additional Locations: India-Haryana, Gurgaon Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. Senior Software Engineer-MLOps We are looking for a highly skilled Senior Software Engineer – MLOps with deep expertise in building and managing production-grade ML pipelines in AWS and Azure cloud environments. This role requires a strong foundation in software engineering, DevOps principles, and ML model lifecycle automation to enable reliable and scalable machine learning operations across the organization Key Responsibilities include: Design and build robust MLOps pipelines for model training, validation, deployment, and monitoring Automate workflows using CI/CD tools such as GitLab Actions, Azure DevOps, Jenkins, or Argo Workflows Build and manage ML workloads on AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena) and Azure (Azure ML Foundry, AKS, ADF, Blob Storage) Design secure and cost-efficient ML architecture leveraging cloud-native services Manage infrastructure using IaC tools such as Terraform, Bicep, or CloudFormation Implement cost optimization and performance tuning for cloud workloads Package ML models using Docker, and orchestrate deployments with Kubernetes on EKS/AKS Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Integrate observability tools for model performance, drift detection, and lineage tracking (e.g., Fiddler, MLflow, Prometheus, Grafana, Azure Monitor, CloudWatch) Ensure model reproducibility, versioning, and compliance with audit and regulatory requirements Collaborate with data scientists, software engineers, DevOps, and cloud architects to operationalize AI/ML use cases Mentor junior MLOps engineers and evangelize MLOps best practices across teams Required Qualification: Bachelor's/Master’s in Computer Science, Engineering, or related discipline 10 years in Devops, with 2+ years in MLOps. Proficient with MLflow, Airflow, FastAPI, Docker, Kubernetes, and Git. Experience with feature stores (e.g., Feast), model registries, and experiment tracking. Proficiency in Devops & MLOps, Automation Cloud formation/Teraform/BICEP Requisition ID: 610750 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

Additional Locations: India-Haryana, Gurgaon Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. Software Engineer-MLOps We are seeking an enthusiastic and detail-oriented MLOps Engineer to support the development, deployment, and monitoring of machine learning models in production environments. This is a hands-on role ideal for candidates looking to grow their skills at the intersection of data science, software engineering, and DevOps. You will work closely with senior MLOps engineers, data scientists, and software developers to build scalable, reliable, and automated ML workflows across cloud platforms like AWS and Azure Key Responsibilities include: Assist in building and maintaining ML pipelines for data preparation, training, testing, and deployment Support the automation of model lifecycle tasks including versioning, packaging, and monitoring Build and manage ML workloads on AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena) and Azure (Azure ML Foundry, AKS, ADF, Blob Storage) Assist with containerizing ML models using Docker, and deploying using Kubernetes or cloud-native orchestrators Manage infrastructure using IaC tools such as Terraform, Bicep, or CloudFormation Participate in implementing CI/CD pipelines for ML workflows using GitHub Actions, Azure DevOps, or Jenkins Contribute to testing frameworks for ML models and data validation (e.g., pytest, Great Expectations). Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Participate in diagnosing issues related to model accuracy, latency, or infrastructure bottlenecks Continuously improve knowledge of MLOps tools, ML frameworks, and cloud practices. Required Qualification: Bachelor's/Master’s in Computer Science, Engineering, or related discipline 7 years in Devops, with 2+ years in MLOps. Good Understanding of MLflow, Airflow, FastAPI, Docker, Kubernetes, and Git. Proficient in Python and familiar with bash scripting Exposure to MLOps platforms or tools such as SageMaker Studio, Azure ML, or GCP Vertex AI. Requisition ID: 610751 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

As a Data Scientist for AI Products at Linde, you will be an integral part of the Artificial Intelligence team within Linde's global corporate division. Your primary responsibility will involve working on real business challenges and opportunities across multiple countries. Your focus will be on supporting the AI team in extending existing AI products and developing new ones to cater to various use cases within Linde's business and value chain. Collaboration with diverse teams including Project Managers, Data Scientists, Data and Software Engineers will be a key aspect of your role. You will directly work with a variety of data sources, types, and structures to derive actionable insights. Developing, customizing, and managing AI software products based on Machine and Deep Learning backends will be among your core tasks. Your role will also entail supporting the replication of existing products and pipelines to other systems and geographies, defining data requirements for new developments, and interacting with business functions to identify opportunities with potential business impact. To excel in this role, you are required to have a Bachelor's or Master's degree in data science, Computational Statistics/Mathematics, Computer Science, Operations Research, or a related field. A strong understanding and practical experience in Multivariate Statistics, Machine Learning, and Probability concepts are essential. Additionally, hands-on experience with preprocessing, feature engineering, data cleansing, and Python programming skills are crucial. Proficiency in handling large datasets using SQL, knowledge of data architectures, and experience with data visualization tools like Tableau or PowerBI are desired. Your result-driven mindset, excellent communication skills, and ability to structure projects from ideation to implementation will be valuable assets in this role. Fluency in English is a must, and any experience with DevOps, MS Azure, Azure ML, Kedro, Airflow, MLflow, or similar tools will be advantageous. Working at Linde offers you the opportunity to be part of a leading global industrial gases and engineering company with a strong commitment to sustainable development and customer success. If you are looking for a challenging yet rewarding career where you can make a positive impact on the world, Linde provides limitless possibilities for your professional growth. Join us in our mission to make the world more productive and sustainable. Let's talk about how you can contribute to our team!,

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

AI Model Development & Support : Assist in fine-tuning LLMs and building innovative, prompt-driven solutions using Azure OpenAI. Develop robust data preprocessing pipelines, focusing on data cleaning, tokenization, and normalization. Contribute to the implementation of RAG pipelines and Azure Document Intelligence solutions. MLOps & Lifecycle Management : Support the implementation and maintenance of Azure ML Pipelines, leveraging MLflow and DVC for efficient version control and experiment tracking. Assist in monitoring AI model performance using Azure Monitor and Application Insights to ensure optimal operation. Maintain and manage AI notebooks and experiments effectively within Azure AI Studio (Foundry). Collaboration & Continuous Learning : Work closely with Senior AI Engineers, Data Scientists, and teams like DataOps and PlatformOps. Actively participate in peer reviews, knowledge-sharing sessions, and documentation efforts to foster a collaborative environment. Seize every opportunity to strengthen your AI and MLOps competencies, contributing to your professional growth. Quality Assurance & Delivery Support : Ensure high code quality, adherence to documentation standards, and timely delivery of project milestones. Contribute to rigorous testing, validation, and seamless integration of AI solutions into production environments. (ref:hirist.tech)

You are a Java Developer with AI/ML experience, required to have at least 5+ years of industry experience in Java, Spring Boot, Spring Data, and a minimum of 2 years of AI/ML project or professional experience. You should possess a strong background in developing and consuming REST APIs and asynchronous messaging using technologies like Kafka or RabbitMQ. Your role involves integrating AI/ML models into Java services or making calls to external ML endpoints. You need to have a comprehensive understanding of the ML lifecycle encompassing training, validation, inference, monitoring, and retraining. Familiarity with tools such as TensorFlow, PyTorch, Scikit-Learn, or ONNX is essential. Previous experience in implementing domain-specific ML solutions like fraud detection, recommendation systems, or NLP chatbots is beneficial. Proficiency in working with various data formats including JSON, Parquet, Avro, and CSV is required. You should have a solid grasp of both SQL (PostgreSQL, MySQL) and NoSQL (Redis) database systems. Your responsibilities will include integrating machine learning models (both batch and real-time) into backend systems and APIs, optimizing and automating AI/ML workflows using MLOps best practices, and monitoring model performance, versioning, and rollbacks. Collaboration with cross-functional teams such as DevOps, SRE, and Product Engineering is necessary to ensure smooth deployment. Exposure to MLOps tools like MLflow, Kubeflow, or Seldon is desired. Experience with at least one cloud platform, preferably AWS, and knowledge of observability tools, metrics, events, logs, and traces (e.g., Prometheus, Grafana, Open Telemetry, Splunk, Data Dog, App Dynamics) are valuable skills in this role. Thank you. Aatmesh,

AI DEVELOPER LLM Can Work Description RMgX is a Gurgaon based digital product innovation & consulting firm. Here at RMgX, we design and build elegant, data-driven digital solutions for complex business problems. At the core of solutions crafted by us is a very strong user experience practice to deeply understand the goals and emotions of business and end-users. RMgX is driven by a passion for quality and we strongly believe in our people and their Description : Duties And Responsibilities Design, develop, and deploy AI solutions using Large Language Models (LLMs) such as GPT, LLaMA, Claude, or Mistral. Fine-tune and customize pre-trained LLMs for business-specific use cases. Build and maintain NLP pipelines for classification, summarization, semantic search, etc. Build and maintain vector database pipelines using Milvus, Pinecone, etc. Collaborate with cross-functional teams to integrate LLM-based features into applications. Analyze and improve model performance using appropriate metrics. Stay up-to-date with AI/ML research and integrate new techniques as EXPERIENCE : 12 years of experience in AI/ML development with specific focus on NLP and LLM-based ABILITIES & KNOWLEDGE : Strong hands-on experience in Python and AI/ML libraries (HuggingFace Transformers, LangChain, PyTorch, TensorFlow, etc.) Proficiency in working with closed-source models via APIs (e.g., OpenAI, Gemini) Understanding of prompt engineering, embeddings, and vector databases like FAISS, Milvus or Pinecone. Experience in deploying models using REST APIs, Docker, and cloud platforms (AWS/GCP/Azure) Familiarity with MLOps and version control tools (Git, MLflow, etc.) Knowledge of LLMOps platforms such as LangSmith, Weights & Biases is a plus Strong problem-solving skills, a keen eye for detail, and ability to work in an agile : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related Information : Perks And Benefits Flexible working hours Saturday and Sundays are fixed off Health Insurance and Personal Accident Insurance BYOD (Bring Your Own Device) Benefit Laptop Buyback Scheme (ref:hirist.tech)

About The Role We are seeking a highly motivated and experienced Senior Data Scientist to join our growing data science team. This role is ideal for someone who thrives at the intersection of business and technology, has a strong foundation in machine learning, and can drive impactful AI initiatives from concept to production. The ideal candidate will have exposure to the metal or manufacturing industry and is proficient in working with cloud-based ML solutions (preferably Azure). Key Responsibilities Translate complex business problems into data science solutions by working closely with business stakeholders, product teams, and domain experts. Conduct problem scoping, solution framing, and feasibility assessments to define clear ML project goals and success metrics. Perform in-depth exploratory data analysis (EDA) to uncover hidden insights and relationships in large, high-dimensional datasets. Design and implement robust data preprocessing and feature engineering pipelines, using both structured and unstructured data. Develop and validate scalable, production-grade ML models including traditional ML (Random Forests, Gradient Boosting, SVM) and deep learning models (CNNs, RNNs, Transformers). Deploy, monitor, and maintain ML models in production environments using Azure ML (preferred), AWS Sagemaker, or Google Vertex AI. Implement end-to-end ML pipelines integrating data ingestion, preprocessing, training, evaluation, deployment, and monitoring (MLOps). Write clean, reusable, and well-documented code in Python following industry standards and MLOps principles (e.g., CI/CD, model versioning, automated testing). Use version control (e.g., Git), experiment tracking tools (e.g., MLflow), and containerization (Docker/Kubernetes) where applicable. Present technical concepts, insights, and recommendations to business and technical stakeholders in a clear and effective manner. Lead client engagements and influence decision-making through storytelling, data visualization, and domain-specific insights. Mentor and guide junior data scientists on technical approaches, project planning, and model evaluation. Foster a culture of innovation, collaboration, and continuous learning across cross-functional teams. Qualifications Bachelors or Masters degree in Metallurgy, Mechanical Engineering, Computer Science, Information Technology, or related disciplines from a top-tier institution (IIT/NIT or equivalent). 4+ years of hands-on experience in data science, machine learning, or applied AI. Prior work in manufacturing, metallurgy, or industrial domains is highly desirable. Proven track record of building and deploying machine learning solutions at scale (ref:hirist.tech)

Job Summary We are seeking a highly motivated AI/ML Engineer to design, develop, and deploy machine learning solutions that solve real-world problems. Responsibilities The ideal candidate should have strong foundations in machine learning algorithms, Python programming, and experience with model development, data pipelines, and production deployment in cloud or on-prem Responsibilities : Design and implement machine learning models and AI solutions for business use cases. Build and optimize data preprocessing pipelines for training and inference. Train, evaluate, and fine-tune supervised, unsupervised, and deep learning models. Collaborate with data engineers, product teams, and software developers. Deploy ML models into production using APIs, Docker, or cloud-native tools. Monitor model performance and retrain/update models as needed. Document model architectures, experiments, and performance metrics. Research and stay updated on new AI/ML trends and tools. Required Skills And Experience Strong programming skills in Python (NumPy, Pandas, Scikit-learn, etc. Experience with deep learning frameworks like TensorFlow, Keras, or PyTorch. Solid understanding of machine learning algorithms, data structures, and statistics. Experience with NLP, computer vision, or time series analysis is a plus. Familiarity with tools like Jupyter, MLflow, or Weights & Biases. Understanding of Docker, Git, and RESTful APIs. Experience with cloud platforms such as AWS, GCP, or Azure. Strong problem-solving and communication skills. Nice To Have Experience with MLOps tools and concepts (CI/CD for ML, model monitoring). Familiarity with big data tools (Spark, Hadoop). Knowledge of FastAPI, Flask, or Streamlit for ML API development. Understanding of transformer models (e.g., BERT, GPT) or LLM : Bachelors or Masters degree in Computer Science, Data Science, AI, or a related field. Certifications in Machine Learning/AI (e.g., Google ML Engineer, AWS ML Specialty) are a plus. (ref:hirist.tech)

As a Principal Engineer / Architect at our organization, you will be responsible for combining deep technical expertise with strategic thinking to design and implement scalable, secure, and modern digital systems. This senior technical leadership role requires hands-on architecture experience, a strong command of cloud-native development, and a successful track record of leading teams through complex solution delivery. Your role will involve collaborating with cross-functional teams including engineering, product, DevOps, and business stakeholders to define technical roadmaps, ensure alignment with enterprise architecture principles, and guide platform evolution. Key Responsibilities: Architecture & Design: - Lead the design of modular, microservices-based, and secure architecture for scalable digital platforms. - Define and enforce cloud-native architectural best practices using Azure, AWS, or GCP. - Prepare high-level design artefacts, interface contracts, data flow diagrams, and service blueprints. Cloud Engineering & DevOps: - Drive infrastructure design and automation using Terraform or CloudFormation. - Support Kubernetes-based container orchestration and efficient CI/CD pipelines. - Optimize for performance, availability, cost, and security using modern observability stacks and metrics. Data & API Strategy: - Architect systems that handle structured and unstructured data with performance and reliability. - Design APIs with reusability, governance, and lifecycle management in mind. - Guide caching, query optimization, and stream/batch data pipelines across the stack. Technical Leadership: - Act as a hands-on mentor to engineering teams, leading by example and resolving architectural blockers. - Review technical designs, codebases, and DevOps pipelines to uphold engineering excellence. - Translate strategic business goals into scalable technology solutions with pragmatic trade-offs. Key Requirements: Must Have: - 5+ years in software architecture or principal engineering roles with real-world system ownership. - Strong experience in cloud-native architecture with AWS, Azure, or GCP (certification preferred). - Programming experience with Java, Python, or Node.js, and frameworks like Flask, FastAPI, Celery. - Proficiency with PostgreSQL, MongoDB, Redis, and scalable data design patterns. - Expertise in Kubernetes, containerization, and GitOps-style CI/CD workflows. - Strong foundation in Infrastructure as Code (Terraform, CloudFormation). - Excellent verbal and written communication; proven ability to work across technical and business stakeholders. Nice to Have: - Experience in MLOps pipelines, observability stacks (ELK, Prometheus/Grafana), and tools like MLflow, Langfuse. - Familiarity with Generative AI frameworks (LangChain, LlamaIndex), Vector Databases (Milvus, ChromaDB). - Understanding of event-driven, serverless, and agentic AI architecture models. - Python libraries such as pandas, NumPy, PySpark and support for multi-component pipelines (MCP). Preferred: - Prior experience leading technical teams in regulated domains (finance, healthcare, govtech). - Cloud security, cost optimization, and compliance-oriented architectural mindset. What You'll Gain: - Work on mission-critical projects using the latest cloud, data, and AI technologies. - Collaborate with a world-class, cross-disciplinary team. - Opportunities to contribute to open architecture, reusable frameworks, and technical IP. - Career advancement via leadership, innovation labs, and enterprise architecture pathways. - Competitive compensation, flexibility, and a culture that values innovation and impact.,

As an AI/ML Engineer, you will be a valuable member of our team, contributing to the development of intelligent systems that harness the power of machine learning and artificial intelligence. Your primary responsibilities will include designing, creating, and implementing machine learning models to address a variety of use cases, such as prediction, classification, NLP, and computer vision. You will collaborate closely with diverse teams to deliver innovative solutions that tackle real-world challenges effectively. Your key responsibilities will involve: - Designing and implementing machine learning models and algorithms for different applications. - Analyzing and preprocessing extensive datasets to establish resilient training pipelines. - Staying abreast of the latest advancements in AI/ML through research and integrating relevant techniques into projects. - Training, fine-tuning, and optimizing models to ensure high performance and scalability. - Deploying models into production environments using tools like Docker, Kubernetes, or cloud services (AWS, GCP, Azure). - Working alongside software engineers, data scientists, and product teams to seamlessly integrate AI/ML solutions into applications. - Monitoring model performance in production, continuously iterating for enhancements, and documenting design decisions, code, and models for transparency and reproducibility. Preferred qualifications for this role include: - Proficiency in NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). - Familiarity with deep learning architectures like CNNs, RNNs, GANs, or transformer models. - Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). - Previous contributions to open-source AI/ML projects or publications in relevant conferences/journals. If you are passionate about AI/ML technologies and eager to work on cutting-edge solutions that make a meaningful impact, we encourage you to apply for this exciting opportunity to join our dynamic team.,

DecisionX is pioneering a new category with the world's first Decision AI, an AI Super-Agent that assists high-growth teams in making smarter, faster decisions by transforming fragmented data into clear next steps. Whether it involves strategic decisions in the boardroom or operational decisions across various departments like Sales, Marketing, Product, and Engineering, down to the minutiae that drives daily operations, Decision AI serves as your invisible co-pilot, thinking alongside you, acting ahead of you, and evolving beyond you. We are seeking a dedicated and hands-on AI Engineer to join our Founding team. In this role, you will collaborate closely with leading AI experts to develop the intelligence layer of our exclusive "Agentic Number System." Key Responsibilities - Building, fine-tuning, and deploying AI/ML models for tasks such as segmentation, scoring, recommendation, and orchestration. - Developing and optimizing agent workflows using LLMs (OpenAI, Claude, Mistral, etc.) for contextual reasoning and task execution. - Creating vector-based memory systems utilizing tools like FAISS, Chroma, or Weaviate. - Working with APIs and connectors to incorporate third-party data sources (e.g., Salesforce, HubSpot, GSuite, Snowflake). - Designing pipelines that transform structured and unstructured signals into actionable insights. - Collaborating with GTM and product teams to define practical AI agent use cases. - Staying informed about the latest developments in LLMs, retrieval-augmented generation (RAG), and agent orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph). Must Have Skills - 5-8 years of experience in AI/ML engineering or applied data science. - Proficient programming skills in Python, with expertise in LangChain, Pandas, NumPy, and Scikit-learn. - Experience with LLMs (OpenAI, Anthropic, etc.), prompt engineering, and RAG pipelines. - Familiarity with vector stores, embeddings, and semantic search. - Expertise in data wrangling, feature engineering, and model deployment. - Knowledge of MLOps tools such as MLflow, Weights & Biases, or equivalent. What you will get - Opportunity to shape the AI architecture of a high-ambition startup. - Close collaboration with a visionary founder and experienced product team. - Ownership, autonomy, and the thrill of building something from 0 to 1. - Early team equity and a fast growth trajectory.,