About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Responsibilities: Transform raw and unstructured data into structured, actionable formats for analysis and reporting. Write, optimize, and maintain SQL queries and stored procedures to ensure efficient data retrieval and processing. Design and implement complex SQL queries, including Common Table Expressions (CTEs), window functions, recursive queries, dynamic pivoting and joins, to extract actionable insights from large datasets efficiently. Design, develop, and maintain databases and data pipelines to support analytics and reporting needs. Perform data engineering tasks, including data ingestion, cleaning, and preprocessing. Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights. Develop and implement machine learning (ML) models and natural language processing (NLP) solutions to solve business challenges. Build and monitor key performance indicators (KPIs) for dashboards and reporting tools. Create wireframes and collaborate with stakeholders to design intuitive data visualizations and dashboards. Ensure data integrity and perform quality checks to maintain high standards of accuracy and reliability. Collaborate with cross-functional teams to align data initiatives with business goals. Manage data science projects from ideation to deployment, ensuring timely delivery and measurable impact. Communicate findings and insights effectively through presentations and reports to technical and non-technical audiences/ stakeholders. Utilize statistical modelling and data mining techniques to drive decision-making and strategy. Must-Have Skills: Proficiency in SQL and Python/R for data manipulation and analysis. Experience with Machine Learning (ML) and NLP techniques. Strong understanding of EDA and statistical modelling. Hands-on experience with Google Cloud Platform (GCP) and Vertex AI. Excellent communication and presentation skills. Solid grasp of data engineering principles, including ETL processes. Good-to-Have Skills: Knowledge of data mining techniques. Knowledge of generative AI tools and frameworks for tasks such as synthetic data generation and data augmentation. Familiarity with dashboard wireframe creation tools and methods. Ability to build or derive KPIs for visualization dashboards. Expertise in Excel for advanced calculations and analysis. Background in project management, including Agile or similar methodologies. Experience in cross-functional team collaboration. Hands-on experience fine-tuning or deploying pre-trained Gen AI models (e.g., Hugging Face Transformers, OpenAI APIs).

Role & responsibilities Architect and implement Al solutions utilizing cutting-edge technologies like LLM, Langchain, and Machine Learning. AIML solution development in Azure using Python Ability to build and finetune the model to improve the performance Create own technology if off-the-shelf technology is not solving the problem. E.g changes to traditional RAG approaches, finetune LLM, create architectures. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Create end to end AI systems with responsible AI principles Preferred candidate profile

*Design and deploy ML models* to score trader performance, risk exposure, and funding eligibility in real-time. Build AI systems to: * Auto-journal trades and classify PnL events * Detect trader manipulation, bots, or copy trading behavior * Identify high-potential traders early (funding prioritization) Use LLMs and NLP to create smart summaries, trade notes, and insights from user behavior and support queries. Own the *AI infrastructure*, from experimentation to production (Docker, APIs, CI/CD). Collaborate closely with our backend, frontend, and R\&D teams to bring AI features into the trader dashboards and CRM. Constantly explore new AI tools, algorithms, and research relevant to fintech and trading ecosystems. *Ideal Candidate Profile* *4+ years of hands-on experience* in building and deploying ML/AI models in production environments. Solid foundation in *machine learning, deep learning, and statistics*. Expertise with tools like *Python, PyTorch/TensorFlow, Scikit-learn, XGBoost, HuggingFace*, etc. Strong data pipeline and API experience (Airflow, FastAPI/Flask, Pandas, SQL, MongoDB). Comfortable with deploying ML models at scale using *Docker, MLflow, AWS/GCP*. Bonus: Experience in *fintech, trading platforms, fraud detection, or real-time data systems*. Bonus++: Knowledge of reinforcement learning, anomaly detection, or building recommender systems. --- What Youll Build (Example Projects) *Traderscore AI*: A real-time rating engine to predict trader potential and risk based on behavior patterns. *AnomalyBot*: A system that flags suspicious trades and prevents fraud before payout. *Smart Journal*: NLP-powered auto trade logs with emotional sentiment tracking and decision reviews. *TopTraderRadar*: Predictive analytics dashboard to identify breakout talent globally.

We are seeking an experienced AI/ML Specialist with a strong background in Natural Language Processing (NLP), Large Language Models (LLM), and Text-to-Speech (TTS) technologies. The ideal candidate will have a proven track record of designing and implementing AI/ML solutions, developing NLP pipelines, fine-tuning large language models, and working with TTS systems. This role offers the opportunity to work on cutting-edge AI-driven projects that have a transformative impact across industries.

Job Position Title: Associate_AI/ML Developer_MS Engg_Advisory_Kolkata Responsibilities : Experience: 3-7 years in AI/ML development, with a demonstrated track record of deploying AI models in Azure App Services / Azure Kubernetes Service (AKS). Desired profile: AI Frameworks/Services: Thorough understanding of frameworks such as Lang-Chain, Semantic Kernel, Py-Torch, Scikit-learn, and cloud services like Azure Cognitive Services, including Azure Machine Learning and Azure Bot Services. Programming : Proficiency in TypeScript and C#, with experience in building applications using the Microsoft .NET framework and experience integrating AI solutions with Microsoft Teams and Microsoft Graph API. NLP Expertise: Experience working with Large Language Models (LLMs), Vectorization, Prompt engineering & Tuning, along with familiarity with Azure Text Analytics. Data Engineering: Strong understanding of data preprocessing, feature engineering, and proficiency in handling both structured and unstructured data, utilizing Azure Data Factory and Azure SQL Database. Cloud Technologies: Experience with Azure DevOps for CI/CD processes and version control, as well as familiarity with Azure Blob Storage for data storage solutions. Mandatory skill sets: AI/ML Developer Preferred skill sets: Deployment of AI models in Azure App Services / Azure Kubernetes Service (AKS). Years of experience required: 3-7 Years Education qualification: B.Tech/B.E./MCA

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama.

We are looking for an AI Engineer (Senior Software Engineer). Interested candidates email me resumes on mayura.joshi@lionbridge.com OR WhatsApp on 9987538863 Responsibilities: Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks. Implement and fine-tune models to improve response relevance and contextual accuracy. Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding. Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities. Integrate AI models with enterprise applications and APIs. Optimize model inference for performance and scalability. Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives. Ensure ethical AI implementation, addressing bias, explainability, and data security. Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques. Requirements: 8+ years experience in software development according to development standards. Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain. Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies. Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate. Solid understanding of NLP, deep learning, and transformer architectures. Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.). Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments. Strong problem-solving and debugging skills. Excellent communication and teamwork abilities Bachelors or Masters degree in computer science, AI, Machine Learning, or a related field.

We are seeking an experienced and innovative AI Specialist to join our dynamic team. The ideal candidate will possess deep expertise in artificial intelligence, machine learning, and neural networks, with a proven track record of designing, developing, and deploying AI solutions. The candidate should be adept at analyzing large datasets, developing optimized algorithms, and integrating AI models into production environments. This role offers the opportunity to contribute to cutting-edge AI applications that solve real-world problems and drive business value Key Responsibilities: AI System Design & Development: Design, develop, and implement AI systems and applications, including machine learning models, neural networks, and natural language processing (NLP) algorithms. Create and optimize AI algorithms for tasks such as image recognition, speech processing, and predictive analytics. Data Analysis & Feature Engineering: Analyze large datasets to identify trends, patterns, and actionable insights. Perform data preprocessing, data wrangling, and feature engineering to enhance model performance. Model Training & Optimization: Train and fine-tune machine learning models using labeled and unlabeled data to improve model accuracy and efficiency. Continuously monitor and optimize models for better performance. AI Model Integration: Deploy machine learning models into production environments, ensuring scalability and reliability. Integrate AI technologies with existing software and business processes using REST APIs. Utilize Docker and Kubernetes to containerize and manage AI models. Research & Innovation: Stay up to date with the latest advancements in AI and machine learning technologies. Explore and experiment with new AI applications, tools, and methodologies to enhance system capabilities. Collaboration & Agile Development: Work closely with cross-functional teams in an Agile environment to develop AI-driven solutions that meet business requirements. Communicate findings and results to stakeholders, ensuring AI solutions align with business goals. Primary Skills and Qualifications: AI and Machine Learning Expertise: Strong knowledge of supervised and unsupervised learning techniques, including classification, regression, clustering, and reinforcement learning. Hands-on experience developing and deploying machine learning models in production environments. Technical Proficiency: Programming Languages: Advanced proficiency in Python, with additional experience in R and SQL as a plus. ML Libraries/Frameworks: Expertise in TensorFlow, PyTorch, and scikit-learn. Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for model deployment and management. Model Deployment & Integration: Familiarity with REST APIs, Docker, and Kubernetes for seamless model integration. Secondary Skills and Preferred Qualifications: Natural Language Processing (NLP): Experience with NLP frameworks such as NLTK, spaCy, Hugging Face, and BERT. Agile Methodologies: Knowledge of Agile practices, with experience using tools like JIRA for project management. Mathematics and Statistics: Strong foundation in probability, statistics, and linear algebra to support model development and evaluation. Data Handling & Preprocessing: Proficiency in data cleaning, transformation, and feature engineering to prepare data for modeling.

Responsibilities : - Design and Development : Architect, design, and develop user-friendly and scalable AI-powered applications using React.js for the frontend and Node.js for the backend. - Generative AI Implementation : Implement, integrate, and fine-tune Generative AI models (e.g., text generation, image synthesis) for specific application requirements. - API Development and Integration : Develop and consume RESTful and GraphQL APIs to facilitate communication between frontend applications and AI/ML models and backend services. - LLM and NLP Integration : Leverage Large Language Models (LLMs) and Natural Language Processing (NLP) techniques to enhance application features and user interactions. - Machine Learning Frameworks : Utilize and integrate various machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) as needed for specific AI functionalities. - Performance Optimization : Optimize AI models and application code for performance, scalability, reliability, and cost-effectiveness. - Collaboration : Collaborate effectively with data scientists, machine learning engineers, backend developers, product managers, and designers throughout the development lifecycle. - Code Quality and Best Practices : Write clean, well-documented, and testable code, adhering to best practices and contributing to CI/CD pipelines for continuous integration and deployment. - Research and Innovation : Stay abreast of the latest advancements in Generative AI, Large Language Models, NLP, web development technologies, and industry trends. Proactively explore and propose new technologies and approaches to enhance our products. - Problem Solving : Troubleshoot and resolve technical issues related to AI model integration, application performance, and API interactions. - Documentation : Create and maintain comprehensive technical documentation for developed components and systems. Qualifications : - Education : Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field. - Experience : [Specify the desired years of experience - e.g., 2-5 years] of professional experience in full-stack development with a focus on frontend (React.js) and backend (Node.js) technologies. - Frontend Expertise : Proven experience in developing responsive and dynamic user interfaces using React.js, including state management libraries (e.g., Redux, Zustand, Context API), component-based architecture, and modern JavaScript (ES6+). - Backend Expertise : Solid experience in developing robust and scalable backend applications using Node.js and frameworks like Express.js or NestJS. - API Development : Strong understanding and practical experience in designing and implementing RESTful and/or GraphQL APIs. - AI/ML Fundamentals : Familiarity with fundamental concepts of Artificial Intelligence and Machine Learning, including different types of models and their applications. - Generative AI Exposure : Experience with implementing or fine-tuning Generative AI models (e.g., using libraries or cloud-based services). - LLM and NLP Knowledge : Understanding of Large Language Models (LLMs) and Natural Language Processing (NLP) concepts and their practical applications. - Machine Learning Frameworks (Desirable) : Familiarity with one or more machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. - Database Knowledge : Experience working with various database systems (e.g., PostgreSQL, MySQL, MongoDB). - DevOps Practices : Understanding of CI/CD pipelines and experience with relevant tools (e.g., Jenkins, GitLab CI/CD, GitHub Actions). - Testing : Experience with writing unit, integration, and end-to-end tests. - Problem-Solving Skills : Excellent analytical and problem-solving abilities. - Communication Skills : Strong written and verbal communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences. - Collaboration : Ability to work effectively in a collaborative team environment.

We are looking for a highly skilled and experienced Senior Data Scientist with 3 to 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. ### Roles and Responsibility Contribute to the design and implementation of state-of-the-art AI solutions. Assist in developing and implementing AI models and systems using techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. ### Job Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related field; a Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements.

We are looking for a skilled professional with strong AI Enabled Automation skills and interest in applying AI in the process automation space. The ideal candidate will have 9 to 13 years of relevant experience. This position is based in Bengaluru. ### Roles and Responsibility Develop and implement AI enabled automation solutions aligned with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system. Collaborate with cross-functional teams to understand requirements and integrate solutions into cloud environments. Educate team members on best practices and stay updated on the latest tech advancements to bring innovative solutions to projects. Work closely with stakeholders to identify opportunities for process improvements and implement changes using AI technologies. ### Job Requirements Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation. Experience with Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Knowledge of retrieval augmented generation (RAG) and knowledge graph RAG. Experience with multi-agent orchestration, memory, and tool integrations. Experience implementing MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility). Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems – latency, drift, performance metrics. Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. Strong analytical, problem-solving, and critical thinking skills. Ability to work under tight timelines for multiple project deliveries.

We are looking for a highly skilled and experienced AI Engineer with 2 to 7 years of experience to join our team in Bengaluru. The ideal candidate will have a strong background in artificial intelligence, machine learning, and software engineering. ### Roles and Responsibility Design, develop, and deploy AI models and systems that align with business objectives. Conduct data analysis, pre-processing, and feature engineering to ensure high-quality input for AI algorithms. Train, evaluate, and optimize AI models using various machine learning algorithms and techniques. Implement scalable and efficient AI solutions in production environments, considering performance, latency, and reliability. Collaborate with AI and software engineers to integrate AI models into production systems and monitor their performance. Analyze and interpret AI model outputs, providing insights and recommendations to stakeholders. ### Job Requirements Deep understanding of AI and machine learning algorithms, including regression, classification, clustering, and deep learning. Proficiency in Python for AI model development, along with experience in deep learning frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with cloud platforms, preferably Azure, to deploy scalable AI solutions, and knowledge of distributed computing frameworks like Spark. Strong foundation in software engineering practices, including version control with Git, testing, documentation, and code review. Understanding of NLP techniques and frameworks such as Hugging Face's Transformers, BERT, GPT, or Transformer models, TensorFlow's NLP library, or spaCy for language-related AI applications. Experience with natural language processing (NLP) techniques and frameworks, and generative AI techniques, including prompt engineering and fine-tuning LLMs. Proficiency in data pre-processing, visualization, SQL, and big data technologies, along with strong skills in Python for AI model development and implementation. Knowledge of containerization tools like Docker and an understanding of responsible AI practices and data privacy. Generative AI Techniques: Knowledge and experience in Generative AI techniques, prompt engineering, vector database, LLMs such as OpenAI, Azure OpenAI, Open-source LLMs. Fine-tuning: Collaborate with the research and development teams to fine-tune large language models using prompts, ensuring the models produce accurate, contextually relevant, and safe responses. Model Evaluation and Optimization: Experience with model evaluation, hyperparameter tuning, and optimization techniques. Data Pre-processing and Visualization: Solid understanding of techniques for data pre-processing, feature engineering, and data visualization. Cloud Platforms: Familiarity with cloud platforms like AWS, Azure, or GCP for scalable AI solutions. (Azure preferred) Distributed Computing: Knowledge of distributed computing frameworks, particularly Spark, for large-scale data processing. Version Control Systems: Proficient in using version control systems like Git for collaborative AI development. Troubleshooting and Debugging: Ability to troubleshoot and debug complex AI systems and models. Containerization: Knowledge of containerization tools like Docker for efficient deployment of AI solutions. Software Engineering Practices: Familiarity with software engineering practices, including testing, documentation, and code review.

We are looking for a highly skilled and experienced Associate Consultant to join our team in Hyderabad. The ideal candidate will have 3-6 years of relevant experience in auditing and accounting standards, with a strong background in financial reporting and analytics. ### Roles and Responsibility Conduct operational, financial, process, and systems audits to review and appraise activities, systems, and controls. Identify accounting and auditing issues, discuss them with the audit in-charge, and solve problems as they arise. Perform substantive testing of appliances according to the audit plan and document all work performed. Present audit reports clearly highlighting key recommendations to management. Prepare and maintain statutory books of accounts, conduct audits, reconcile account receivables and payables, and finalize accounts. Assist seniors in reviewing and checking financial statements and preparing audit reports, management comment letters, and management representation letters. ### Job Requirements Strong knowledge of auditing and accounting standards is required. Experience in handling statutory audit assignments is necessary. Ability to prioritize work on multiple assignments and manage ambiguity effectively. Strong verbal and communication skills are essential. Clarity of thoughts and assertive, effective, and creative written expression (logical, readable, and concise) are vital. Ability to meet deadlines and deliver insightful solutions to complex problems. Qualification: BE/ B.Tech,, or MSC in Computer Science/Statistics or M.C.A. Skills and attributes for success include technical excellence, audit analytics, and data extraction from client ERPs. Hands-on experience in analytics in financial reporting, machine learning using R or Python with a strong statistical background, and knowledge of databases, ETL, and hands-on experience in SQL. Experience in any of the visualization tools like Tableau, Spotfire, Qlikview, etc., and knowledge and experience in ERP such as SAP and/or Oracle and data extraction. Proficiency in MS Office Suite (advanced Excel skills & Macros) is expected. Experience in NLP/Web Scraping/Log Analytics/TensorFlow/AI/Beautiful Soup is preferred. Experience in Iron Python/JavaScript is a plus.

We are looking for a highly skilled and experienced Associate Consultant to join our team in Hyderabad. The ideal candidate will have 3-6 years of experience in auditing and accounting standards, with a strong background in financial reporting and analytics. ### Roles and Responsibility Conduct operational, financial, process, and systems audits to review and appraise activities, systems, and controls. Identify accounting and auditing issues, discuss them with the audit in-charge, and resolve problems as they arise. Perform substantive testing of appliances according to the audit plan and document all work performed. Present audit reports clearly highlighting key recommendations to management. Prepare and maintain statutory books of accounts, conduct audits, reconcile account receivables and payables, and finalize accounts. Assist seniors in reviewing and checking financial statements and preparing audit reports, management comment letters, and management representation letters. ### Job Requirements Strong knowledge of auditing and accounting standards is required. Experience in handling statutory audit assignments is necessary. Ability to prioritize work on multiple assignments and manage ambiguity effectively. Strong verbal and communication skills are essential. Clarity of thoughts and assertive, effective, and creative written expression (logical, readable, and concise) are vital. Ability to meet deadlines and deliver insightful solutions to complex problems. Must have handled statutory audit assignments earlier. Knowledge of databases, ETL, and hands-on experience or theoretical knowledge in SQL. Experience in any of the visualization tools like Tableau, Spotfire, Qlikview, etc. Knowledge and experience in ERP such as SAP and/or Oracle and data extraction. Proficiency in MS Office Suite (advanced Excel skills & Macros). Experience in NLP/ Web Scraping/ Log Analytics/ TensorFlow/ AI / Beautiful Soup. Experience in Iron Python/JavaScript. Qualification: BE/ B.Tech,, or MSC in Computer Science/Statistics or M.C.A.

We are looking for an AI & Machine Learning Lead Engineer to lead the development and deployment of advanced AI and machine learning models. The ideal candidate will have a strong background in precision learning, large language models (LLMs), retrieval-augmented generation (RAG), natural language processing (NLP), and statistical methods for output analysis. This role involves leading a team of engineers and data scientists, setting strategic directions for AI/ML initiatives, and ensuring the delivery of impactful solutions that align with our business objectives. Key Responsibilities: Leadership and Strategy: Lead and manage a team of AI and machine learning engineers, providing technical guidance and mentorship. Oversee the entire machine learning lifecycle, from data collection and preprocessing to model training, evaluation, and deployment. Develop and drive the AI/ML strategy, aligning it with overall business goals. Collaborate with cross-functional teams, including data engineering, product management, and software development, to integrate ML models into production environments. Precision Learning and Large Language Models (LLMs): Design, develop, and optimize precision learning algorithms for specific business applications. Lead efforts in developing, fine-tuning, and deploying large language models (LLMs) to address various use cases such as text generation, summarization, translation, and conversational AI. Retrieval-Augmented Generation (RAG): Implement and optimize RAG systems to improve the performance and accuracy of AI solutions. Develop retrieval strategies that effectively integrate large-scale knowledge bases with LLMs to generate more accurate and contextually relevant outputs. Natural Language Processing (NLP): Develop and implement NLP models for tasks such as text classification, sentiment analysis, named entity recognition, summarization, and question-answering. Stay current with NLP research trends and advancements, implementing best practices to enhance model efficiency and performance. Output Analysis through Statistical Methods: Analyse model outputs using advanced statistical methods to ensure reliability, accuracy, and explainability. Implement A/B testing, hypothesis testing, and other statistical techniques to validate model performance and derive actionable insights. Research and Development: Stay abreast of the latest research in machine learning, deep learning, and AI. Propose and implement novel approaches to solve challenging problems. Collaborate with academic and research institutions to contribute to the machine learning community through publications, open-source projects, and conferences MLOps and Model Deployment: Collaborate with DevOps and data engineering teams to implement MLOps practices for CI/CD pipelines, model monitoring, and governance. Ensure scalable deployment of AI/ML models on cloud platforms (AWS, GCP, Azure) or on-premises environments. Mentorship and Team Leadership: Mentor and guide a team of machine learning engineers and data scientists, fostering a culture of continuous learning and innovation. Conduct regular code reviews, provide constructive feedback, and ensure adherence to best practices in machine learning. Required Qualifications: 8-10 years Experience with Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field; PhD is a plus. 5+ years of experience in machine learning and AI, with a strong focus on NLP, LLMs, RAG, and precision learning. Proven track record of leading AI/ML teams and projects from conception to deployment. Expertise in Python and relevant ML libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers. Strong understanding of NLP techniques, including transformer architectures (e.g., BERT, GPT). Experience in RAG techniques, knowledge retrieval systems, and integrating LLMs with external data sources. Proficiency in statistical analysis and hypothesis testing, with a strong foundation in experimental design. Excellent problem-solving skills, with the ability to articulate complex technical concepts to non-technical stakeholders. Preferred Qualifications: Experience with cloud services (AWS, GCP, Azure) for model deployment and scaling. Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD pipelines for ML. Knowledge of advanced AI techniques such as reinforcement learning, meta-learning, and unsupervised learning. Strong publication record or contributions to the AI/ML community.

Objectives of this role Develop and implement solutions/processes and carry out R&D (Research and Development) to meet the needs of our AI/ML strategy. Help in design and development of advanced analytic solutions across functional areas as per requirement/opportunities. Foster innovative ideas for developing high impact solutions. Responsibilities As part of the R&D team, help the team to advise leaders on a broad range of technology, strategy associated with AI (Artificial Intelligence) & ML Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, and support procedures, in collaboration with the team. Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation. Work as team members, develop & assess the AI/ML and automation opportunities. Enable team members/as individual contributors to make necessary changes in product performance or presentation. Develop new and innovative AI/ML based solutions and PoC (Proof of Concept) Must have skills. 6-10 Years of experience in IT including 3+ years in developing / applying ML /AI models to practical and comprehensive technology solutions. Must be graduate in Computer Science preferably B. Tech/B.E. or MCA etc. Experience with ML, deep learning, TensorFlow, Python, NLP, Azure services. Knowledge of basic algorithms, object-oriented and functional design principles, and best- practice patterns. Experience in API development/consumption. NoSQL/RDBMS database design and optimizations. Open and willing to learn & work in any technology. Good to Have Skills Good to have knowledge of any other programming and/or scripting language. Exposure to Cloud technology like AWS (Amazon Web Services) / GCP (Google Cloud Platform). Experience with visualization tools (e.g., Power BI, Tableau etc.) Experience in Healthcare sector e.g. RCM

The Team: As a Senior Lead Machine Learning Engineer of the Document Platforms and AI Team, you will play a critical role in building the next generation of data extraction tools, working on cutting-edge ML-powered products and capabilities that power natural language understanding, information retrieval, and data sourcing solutions for the Enterprise Data Organization and our clients. This is an exciting opportunity to shape the future of data transformation and see your work make a real difference, all while having fun in a collaborative and engaging environment. You'll spearhead the development and deployment of production-ready AI products and pipelines, leading by example and mentoring a talented team. This role demands a deep understanding of machine learning principles, hands-on experience with relevant technologies, and the ability to inspire and guide others. You'll be at the forefront of a rapidly evolving field, learning and growing alongside some of the brightest minds in the industry. If you're passionate about AI, driven to make an impact, and thrive in a dynamic and supportive workplace, we encourage you to join us! The Impact: The Document Platforms and AI team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Responsibilities: Build production ready data acquisition and transformation pipelines from ideation to deployment. Being a hands-on problem solver and developer helping to extend and manage the data platforms. Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions Technical leadership: Drive the technical vision and architecture for the extraction project, making key decisions about model selection, infrastructure, and deployment strategies. Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains. Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training. Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability. Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability. Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process. Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions. Code quality and best practices: Ensure high code quality and adherence to best practices for software development. Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences. What Were Looking For: 8-10 years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face) Experience with Apache Spark or other distributed computing frameworks for large-scale data processing. AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks. Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models . Experience with CI/CD pipelines for ML models, including automated testing and deployment. Docker & Kubernetes experience for containerization and orchestration. OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Excellent Problem-solving, Code Review and Debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Core Java 17+, preferably Java 21+, and associated toolchain Apache Avro Apache Kafka Other JVM based languages - e.g. Kotlin, Scala C# - in particular .NET Core

Role description We are seeking an experienced Gen AI and LLM Developer to design, develop, and deploy generative AI models and large language models (LLMs) for advanced natural language processing (NLP) tasks. The ideal candidate will have 6-9 years of experience with LLM architectures (e.g., GPT, BERT), deep learning frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure). Responsibilities include training and fine-tuning models, optimizing for performance, collaborating with cross-functional teams, and staying updated on the latest AI trends. Strong technical skills in Python, NLP techniques, model optimization, and distributed training are essential. Experience designing scalable system with Generative AI" and "Exposure to full stack development on .net or Java based platform

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Summary: As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves creating cloud or on-prem application pipelines with production-ready quality, incorporating deep learning, neural networks, chatbots, and image processing. Location: Pan India

Responsibilities: * Design generative AI solutions using LLM, Python, SQL & NLP techniques. * Collaborate with cross-functional teams on project delivery. * Implement RNN, LSTM, GRU models for text analysis.

Job Title: Machine Learning Engineer (Computer Vision + GenAI) Location: Bangalore, India (Hybrid) Company: Factspan Analytics Client Industry: Retail / E-commerce About the Role We are looking for a highly skilled Machine Learning Engineer with a strong foundation in Computer Vision , NLP , and GenAI to join our team at Factspan. You'll work closely with a leading retail client to address a critical business challenge: identifying and resolving duplicate product listings across Marketplace and traditional sellers using AI-driven solutions. This role is central to helping the client clean up and scale their product catalog across 30+ categories, each with 10,000+ images. You'll be expected to build and productionize models that can intelligently compare product images and text descriptions to detect duplicates and inconsistencies, leveraging both traditional ML and the latest GenAI techniques. Key Responsibilities Build and deploy scalable Computer Vision pipelines to identify near-duplicate product images across millions of listings. Use Natural Language Processing to match product descriptions and titles with associated images. Leverage LLMs and multimodal GenAI models (e.g., BLIP, CLIP, LLaVA, Gemini, GPT-4V) to solve alignment problems between images and text. Design and implement MLOps and LLMOps pipelines for deploying both traditional ML models and GenAI solutions in production. Perform large-scale image embedding generation , storage, and similarity search using tools like FAISS , Milvus , or pgvector . Use BigQuery and write optimized SQL queries for data preprocessing and analytics. Collaborate with product managers, data engineers, and cloud architects to scale the solution across new product categories. Required Skills 6+ years of hands-on experience in Machine Learning or Data Science roles. Deep expertise in Computer Vision (image deduplication, embedding models, similarity search). Strong understanding of NLP with experience aligning image and text modalities. Exposure to Generative AI/LLMs and how they can be used in multimodal tasks. Experience deploying ML/GenAI models using MLOps/LLMOps best practices (CI/CD, monitoring, versioning). Proficient in Python , TensorFlow/PyTorch , OpenCV , and transformers libraries (e.g., Hugging Face). Familiarity with GCP ecosystem especially BigQuery , Cloud Storage , Vertex AI , Cloud Functions . Strong SQL skills and understanding of data pipelines. Previous experience growing from a Data Scientist role is highly desirable. Good to Have Hands-on with Vector Databases like Milvus, Pinecone, or pgvector. Knowledge of retrieval-augmented generation (RAG) pipelines for GenAI solutions. Familiarity with tools like LangChain , Unstructured.io , or Haystack . Understanding of image compression, image hashing, and perceptual similarity techniques. Why Join Us Work on a high-impact retail AI problem at enterprise scale. Collaborate with a forward-thinking client open to innovation. Join a team where your work directly translates to business value. Flexible hybrid working model in Bangalore with a passionate AI team. Ready to create innovative solutions with computer vision, NLP, and GenAI in retail? Apply now by sending your resume and cover letter to sathishkumar.arumugam@factspan.com.

Responsibilities: Extract insights & build models to understand /predict Key metrices Work closely with stakeholders to identify business challenges and translate them into data science problems. Collect, clean, and preprocess structured and unstructured data from various sources. Focuses on Research Analysis, model development. Building models (regression, classification, clustering. Etc.) validate and deploy machine learning models to solve real-world business problems. Perform statistical analysis and generate data-driven insights and recommendations. Collaborate with engineering and product teams to implement data solutions. Automate monitoring model performance and retraining. Bachelor's or master's degree in computer science, Data Science, Statistics, Mathematics, or a related field. 5+ years of experience in a data science or machine learning role. Strong Python (PySpark, pandas, scikit-learn, TensorFlow/PyTorch). Hands-on with MLflow for model tracking & deployment. Expertise in Databricks for scalable ML workflows. Expertise in handling data issues including data gaps, duplicates, data drifts etc. Strong SQL skills and experience working with large databases. Solid understanding of statistical modelling, A/B testing, and predictive analytics. Strong grasp of supervised/unsupervised learning, deep learning, and optimization techniques. Experience with A/B testing and model performance monitoring. Experience with cloud platforms (AWS, GCP, or Azure) and working knowledge of MLOps is a plus. Excellent problem-solving skills, communication skills, and attention to detail. Experience deploying models to production using CI/CD pipelines.

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

About the Role Were looking for a passionate AI Evangelist & Code Generation Expert to lead the adoption of AI-powered coding tools across our engineering teams. In this pivotal role, you’ll drive a transformation in how we build software—spanning new development, code refactoring, test generation, tech stack and microservice migration. You'll champion tools like Cursor AI, GitHub Copilot, and Windsurf AI, deliver impactful training, and demonstrate measurable gains in productivity and code quality. Experience applying AI in our domain is a strong plus. Key Responsibilities Champion AI-Powered Coding : Advocate the adoption of tools like Cursor AI, GitHub Copilot, and Windsurf AI across engineering teams, articulating their value and addressing resistance. Drive Training & Enablement : Design tailored training sessions, workshops, and resources to onboard developers at all levels and promote effective tool usage. Lead Adoption & Strategy : Build strategies to integrate AI tools into dev workflows, track adoption, and identify improvement areas. Set Standards & Best Practices : Establish clear usage guidelines ensuring code quality, security, and maintainability. Promote High-Impact Use Cases : Apply AI to areas like app development, code refactoring, tech stack migration, test generation, and microservice transformation. Measure ROI : Define and track metrics like dev velocity and bug reduction to demonstrate impact and adoption success. Provide Ongoing Support : Be the go-to expert for AI coding tools, offering mentorship, troubleshooting, and continuous guidance. Stay Ahead of the Curve : Monitor emerging AI technologies and recommend tools aligned with org goals. Collaborate with Engineering Leaders : Align AI strategy with overall tech objectives in partnership with managers and architects. Domain-Specific AI Use Case Exploration : Explore domain-specific AI opportunities beyond coding, such as Gen AI, NLP, computer vision, or document classification. Qualification & Functional Skills Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related fields. 5+ years of experience in software development with strong knowledge of SDLC, architecture, and testing practices. At least 1 year of hands-on experience with AI-powered coding tools like Cursor AI, GitHub Copilot, or Windsurf AI. Excellent communication and presentation skills; able to evangelize complex concepts to both technical and non-technical audiences. Proven ability to design and deliver impactful technical training sessions and workshops. Strong analytical mindset with the ability to measure and communicate technology impact. Comfortable working independently and collaboratively in a fast-paced, evolving environment. Passionate about emerging technologies, especially in the AI space. Proficient in code refactoring, software design principles, and modern dev tools and frameworks. Preferred : Experience applying AI in domains like Gen AI, classification, computer vision, or NLP. Preferred : Familiarity with cloud platforms (AWS, Azure, GCP) and microservices architecture.