102 Model Deployment Jobs - Page 3

Description We are seeking a skilled Data Scientist with expertise in Machine Learning to join our dynamic team in India. The ideal candidate will have a strong background in developing predictive models and a passion for extracting insights from complex data. This role will involve collaboration with various teams to drive data-driven decision-making. Responsibilities Develop and implement machine learning models to solve business problems. Analyze large datasets to extract meaningful insights and trends. Collaborate with cross-functional teams to define data-driven strategies. Communicate findings and recommendations to stakeholders effectively. Continuously improve models based on feedback and new data. Stay updated with the latest advancements in data science and machine learning. Skills and Qualifications Strong understanding of machine learning algorithms and techniques. Proficiency in programming languages such as Python, R, or Java. Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy). Familiarity with machine learning frameworks (e.g., TensorFlow, Keras, Scikit-learn). Solid understanding of statistics and probability theory. Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work with SQL and NoSQL databases. Strong problem-solving skills and analytical mindset.

Job Title: Machine Learning Engineer (Manager - Band B2/ C1) Company Name: EXL Services Location: Bangalore/Noida/Pune/Hyderabad/Gurgaon/ WFH Mode Education: B.E. / B. Tech / M.E. / M. Tech / MCA Experience Required: 4+ years of relevant experience Job Responsibilities: Model Deployment and Management: Drive ML prototypes into production ensuring seamless deployment and management on cloud at scale. Monitor real-time performance of deployed models, analyze data, and proactively address performance issues. Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability. Collaboration and Integration: Collaborate with DevOps engineers to manage cloud compute resources for ML model deployment and performance optimization. Work closely with ML scientists, software engineers, data engineers, and other stakeholders to implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated deployment. Innovation and Continuous Improvement: Stay updated with the latest advancements in MLOps technologies and recommend new tools and techniques. Contribute to the continuous improvement of team processes and workflows. Share knowledge and expertise to promote a collaborative learning environment. Development and Documentation: Build software to run and support machine-learning models. Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes. Participate in fast iteration cycles and adapt to evolving project requirements. Business Solutions and Strategy: Propose solutions and strategies to business challenges. Collaborate with Data Science team, Front End Developers, DBA, and DevOps teams to shape architecture and detailed designs. Mentorship: Conduct code reviews and mentor junior team members. Foster strong interpersonal skills, excellent communication skills, and collaboration skills within the team. Mandatory Skills: Programming Languages: Proficiency in Python (3.x) and SQL. ML Frameworks and Libraries: Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture. Databases: Proficiency in SQL and NoSQL databases. Mathematics and Algorithms: In-depth knowledge of mathematics, statistics, and algorithms. ML Modules and REST API: Proficient with ML modules and REST API. Version Control: Hands-on experience with version control applications (GIT). Model Deployment and Monitoring: Experience with model deployment and monitoring. Data Processing: Ability to turn unstructured data into useful information (e.g., auto-tagging images, text-to-speech conversions). Problem-Solving: Analytically agile with strong problem-solving capabilities. Learning Agility: Quick to learn new concepts and eager to explore and build new features. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Experience: Minimum of 4 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.

Looking for an AI/ML Engineer to build smart automation solutions. Must have experience in Python, Node.js, or Java scripting, and strong knowledge of ML/AI techniques and model integration. Required Candidate profile AI/ML Engineer with 4–8 years of experience in developing intelligent testing solutions. Skilled in Python/Node.js/Java, ML model deployment, automation frameworks, and cloud platforms.

Key Responsibilities: Lead and mentor a team of data scientists to deliver actionable insights and solutions Oversee the design and implementation of machine learning models and data workflows Collaborate with cross-functional teams to address business challenges with data-driven strategies Ensure best practices in data analysis, algorithm development, and model deployment Manage project timelines, resources, and deliverables for successful execution of initiatives Required Qualifications: 4+ years of experience in data science, including 1+ years in a leadership role Strong proficiency in Python, R, SQL, and machine learning frameworks Proven experience in leading data science projects and managing teams Strong problem-solving skills with the ability to translate data into business strategies

Key Responsibilities: Lead and mentor a team of data scientists to deliver actionable insights and solutions Oversee the design and implementation of machine learning models and data workflows Collaborate with cross-functional teams to address business challenges with data-driven strategies Ensure best practices in data analysis, algorithm development, and model deployment Manage project timelines, resources, and deliverables for successful execution of initiatives Required Qualifications: 4+ years of experience in data science, including 1+ years in a leadership role Strong proficiency in Python, R, SQL, and machine learning frameworks Proven experience in leading data science projects and managing teams Strong problem-solving skills with the ability to translate data into business strategies

Contractual (Project-Based) Notice Period: Immediate - 15 Days Fill this form: https://forms.office.com/Pages/ResponsePage.aspx?id=hLjynUM4c0C8vhY4bzh6ZJ5WkWrYFoFOu2ZF3Vr0DXVUQlpCTURUVlJNS0c1VUlPNEI3UVlZUFZMMC4u Resume- shweta.soni@panthsoftech.com

We are looking for a skilled Machine Learning Engineer to join our dynamic team in India. The ideal candidate will have a strong background in machine learning and data analysis, with a proven track record of developing and deploying models that deliver business value. You will work closely with data scientists and software engineers to design innovative solutions that leverage data to drive decision-making. Responsibilities Design and implement machine learning models and algorithms to solve business problems. Collaborate with cross-functional teams to understand requirements and deliver effective solutions. Analyze large datasets to extract insights and improve model performance. Perform data preprocessing and feature engineering to optimize models. Monitor and maintain deployed models to ensure their effectiveness and reliability. Stay updated with the latest trends and advancements in machine learning and AI. Skills and Qualifications 3-6 years of experience in machine learning and data science. Proficiency in programming languages such as Python, R, or Java. Strong understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data manipulation and analysis using libraries such as Pandas and NumPy. Familiarity with SQL and database management systems. Knowledge of data visualization tools like Matplotlib, Seaborn, or Tableau. Strong problem-solving skills and ability to work in a team environment. Good communication skills to convey complex technical concepts to non-technical stakeholders.

Description We are seeking an experienced AI ML Trainer to join our team in India. The ideal candidate will be responsible for designing and delivering training programs on AI and machine learning technologies. You will play a crucial role in enhancing the skills of our teams and ensuring our AI models are effectively trained and evaluated. Responsibilities Design and implement training programs for AI and ML models. Evaluate the performance of AI models and provide feedback for improvement. Collaborate with data scientists and engineers to enhance training methodologies. Develop training documentation and resources for internal and external stakeholders. Conduct workshops and seminars to educate teams on AI and ML best practices. Skills and Qualifications Bachelor's or Master's degree in Computer Science, Data Science, or related fields. 2-3 years of experience in AI/ML training or development. Strong understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Proficiency in programming languages such as Python or R. Experience with data preprocessing, feature engineering, and model evaluation techniques. Excellent communication and presentation skills to convey complex concepts clearly. Ability to work collaboratively in a team environment and mentor junior staff.

We're Hiring: AI/ML Consultant Location: Vijayawada Experience: 510 Years | Type: Full-Time | Industry: Artificial Intelligence, Machine Learning, Data Science Do you have a passion for building intelligent systems that solve real-world problems? Are you skilled in deploying scalable AI/ML models that create business impact? If yes, we’d love to hear from you! Role Overview We are looking for an AI/ML Consultant to develop and integrate intelligent solutions that drive automation, decision-making, and innovation across multiple domains. Key Responsibilities Design and deploy AI/ML models for data-driven solutions Optimize models for scalability, accuracy, and interpretability Integrate AI models with low-code/no-code platforms for business users Work with stakeholders to define AI use cases and encourage adoption Required Skills Proficient in Python, R, and frameworks such as TensorFlow, PyTorch, Scikit-learn Experience in MLOps, model deployment, CI/CD, and version control Knowledge of ethical AI, bias detection, and explainable AI techniques Hands-on experience with AI-driven automation, chatbots, and decision support systems Preferred Certifications Certified AI/ML Engineer (AWS, Google Cloud, Microsoft) TensorFlow Developer Certificate Certification in AI Ethics & Governance

Essential functions Design, train, fine-tune, and optimize local LLMs or other NLP models for PII detection across diverse data types (documents, databases, knowledge graphs, code, and other knowledge-sharing formats). Develop generative AI agents (on Autogen/Langgraph) for schema- and metadata-based PII detection to enhance identification of sensitive data. Work with cutting-edge AI frameworks (Ray, llama.cpp, ollama, vLLM, PyTorch) to deploy and scale models efficiently in a distributed environment. Implement and optimize AI/ML solutions on Azure cloud and on-premise infrastructure, ensuring high performance and reliability. Collaborate with data engineering, security, and compliance teams to align AI solutions with business needs and regulatory requirements. Lead a small team of AI engineers, providing mentorship, code reviews, and technical guidance to drive project success. Maintain and monitor model performance, retraining models on a quarterly or monthly basis to handle 50+ PB of evolving data and to improve accuracy over time. Ensure AI models follow best practices and compliance standards, adhering to security requirements and regulations (GDPR, CCPA, PCI DSS, etc.). Qualifications Strong experience with AI frameworks such as Ray, llama.cpp, ollama, vLLM, and PyTorch for building and scaling LLM solutions. Expertise in LLM fine-tuning and prompt engineering, including techniques like Reinforcement Learning from Human Feedback (RLHF) to refine model outputs. Hands-on experience with AI model deployment in Azure cloud environments as well as on-premises servers. Familiarity with large-scale data (50+ PB) and distributed computing paradigms (e.g., using clusters or Ray) to handle massive datasets. Familiarity with MCP (Model Context Protocol) Servers and securing them. Strong programming skills in Python, with experience in machine learning frameworks and libraries. Ability to work cross-functionally with stakeholders in security, compliance, and data engineering to incorporate their requirements into AI solutions. Strong awareness if not implementation experience with Differential Privacy/Federated Learning. Excellent communication skills, with the ability to explain complex AI concepts and results to non-technical teams and leadership clearly. Would be a plus Proven experience leading small AI/ML teams, with a track record of delivering projects and mentoring team members. Knowledge of data security and compliance frameworks, as well as experience with responsible AI practices (ethical AI, bias mitigation, data privacy). Background in financial, payments, or security-related AI applications, giving you insight into the challenges and standards of the fintech industry.

Essential functions Design, train, fine-tune, and optimize local LLMs or other NLP models for PII detection across diverse data types (documents, databases, knowledge graphs, code, and other knowledge-sharing formats). Develop generative AI agents (on Autogen/Langgraph) for schema- and metadata-based PII detection to enhance identification of sensitive data. Work with cutting-edge AI frameworks (Ray, llama.cpp, ollama, vLLM, PyTorch) to deploy and scale models efficiently in a distributed environment. Implement and optimize AI/ML solutions on Azure cloud and on-premise infrastructure, ensuring high performance and reliability. Collaborate with data engineering, security, and compliance teams to align AI solutions with business needs and regulatory requirements. Lead a small team of AI engineers, providing mentorship, code reviews, and technical guidance to drive project success. Maintain and monitor model performance, retraining models on a quarterly or monthly basis to handle 50+ PB of evolving data and to improve accuracy over time. Ensure AI models follow best practices and compliance standards, adhering to security requirements and regulations (GDPR, CCPA, PCI DSS, etc.). Qualifications Strong experience with AI frameworks such as Ray, llama.cpp, ollama, vLLM, and PyTorch for building and scaling LLM solutions. Expertise in LLM fine-tuning and prompt engineering, including techniques like Reinforcement Learning from Human Feedback (RLHF) to refine model outputs. Hands-on experience with AI model deployment in Azure cloud environments as well as on-premises servers. Familiarity with large-scale data (50+ PB) and distributed computing paradigms (e.g., using clusters or Ray) to handle massive datasets. Familiarity with MCP (Model Context Protocol) Servers and securing them. Strong programming skills in Python, with experience in machine learning frameworks and libraries. Ability to work cross-functionally with stakeholders in security, compliance, and data engineering to incorporate their requirements into AI solutions. Strong awareness if not implementation experience with Differential Privacy/Federated Learning. Excellent communication skills, with the ability to explain complex AI concepts and results to non-technical teams and leadership clearly.

Job Summary: - Data Scientist with good hands-on experience of 3+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. Job Responsibilities: - 1. Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib 2. Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) 3. Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence 4. Good understanding of any of the cloud platform AWS, Azure or GCP 5. Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus 6. Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. 7. Should be able to mentor and guide mid to large sized teams under him/her Job Requirements: - 1. Strong experience on Spark with Scala/Python/Java 2. Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment 3. Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering 4. Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus Qualification: - - B-Tech or BE in Computer Science / Computer Applications from Tier 1-2 college with 3+ years of proven experience in the field of Advanced Analytics or Machine Learning OR - Master's degree in Machine Learning / Statistics / Econometrics, or related discipline from Tier 1-2 college with 3+ years of experience Must have Skills: - Real-world experience in implementing machine learning/statistical/econometric models/advanced algorithms Breadth of machine learning domain knowledge Experience in application of machine learning algorithms (classification, regression, deep learning, NLP, etc.) Experience with a ML/data-centric programming language (such as Python, Scala, or R) and ML libraries (pandas, numpy, scikit-learn, etc.) Experience with Apache Hadoop / Spark (or equivalent cloud-computing/map-reduce framework) Skills that give you an edge: - Strong analytical skills to solve and model complex business requirements are a plus. With life sciences or pharma background. We will provide (Employee Value Proposition) Offer an inclusive environment that encourages diverse perspectives and ideas Deliver challenging and unique opportunities to contribute to the success of a transforming organization Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online Axtria Institute, knowledge sharing opportunities globally, learning opportunities through external certifications Sponsored Tech Talks & Hackathons Possibility to relocate to any Axtria office for short and long-term project

Design, develop, and deploy AI/ML models; build scalable, low-latency ML infrastructure; run experiments; optimize algorithms; collaborate with data scientists, engineers, and architects; integrate models into production to drive business value. Required Candidate profile 5–10 yrs in AI/ML, strong in model development, optimization, and deployment. Skilled in Azure, ML pipelines, data science tools, and collaboration with cross-functional teams.

Job Summary: We are seeking a dynamic and highly knowledgeable AI Trainer to deliver engaging and impactful AI awareness sessions and workshops to students, teachers, and parents in school settings. The ideal candidate will possess deep expertise in Artificial Intelligence, exceptional communication skills, and a passion for making complex AI concepts accessible and exciting for diverse audiences within an Indian educational context. Key Responsibilities: Content Delivery: Conduct interactive AI awareness sessions for students and parents, introducing fundamental AI concepts and their everyday applications. Lead hands-on AI workshops for students (Grades 6-12), focusing on AI literacy, practical tools, and responsible AI use. Facilitate specialized AI workshops for teachers, covering AI integration strategies, ethical AI, and AI academic integrity. Potentially co-conduct combined sessions for students and teachers, fostering a shared understanding of AI's impact. Audience Engagement: Adapt training content and delivery methods to suit various age groups and technical understanding levels (Grade 6-12 students, parents, diverse teaching staff). Utilize engaging pedagogical approaches, including interactive activities, real-world examples (especially those relevant to India), and hands-on demonstrations with AI tools. Foster an inspiring and curiosity-driven learning environment. Knowledge & Expertise: Demonstrate deep knowledge of core AI concepts (Machine Learning, Deep Learning, Generative AI, NLP, Computer Vision). Stay updated with the latest advancements in AI and its applications, particularly in the educational sector. Address ethical considerations of AI, including bias, privacy, and responsible use, in an age-appropriate and culturally sensitive manner. Collaboration & Logistics: Work closely with school coordinators and the program team to ensure smooth workshop logistics, scheduling, and setup. Provide feedback and insights for continuous improvement of the program content and delivery. Academic Integrity Focus: Specifically address AI Academic Integrity with both students and teachers, providing clear guidelines and strategies for ethical AI tool usage in an academic context, aligned with NEP 2020 principles. Requirements Required Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Education Technology, or a related technical field. AI Expertise: Proven, in-depth understanding of AI/ML concepts and their practical applications. Training Experience: Minimum [5] years of experience delivering training or workshops, preferably within educational settings (schools, colleges). Audience Engagement: Demonstrated ability to engage diverse audiences (students of varying ages, parents, teachers) effectively. Communication Skills: Exceptional verbal communication, presentation, and interpersonal skills in English. Proficiency in relevant regional Indian languages is a significant advantage. Pedagogical Skills: Understanding of educational methodologies and the ability to simplify complex technical topics. Adaptability: Flexibility to adapt training content and style based on audience needs and available school resources. Travel: Willingness to travel to various school locations across India. Preferred Qualifications: Prior experience specifically delivering AI training to K-12 students or teachers. Familiarity with the Indian education system and NEP 2020 guidelines. Experience with no-code AI platforms (e.g., Google Teachable Machine) or educational coding environments (e.g., Scratch with AI extensions). Experience with online quiz platforms and virtual engagement tools.

Job Description AI/ML Engineer We are seeking a sharp, innovative, and passionate AI/ML Engineer to join our R&D team. You will be responsible for designing and deploying intelligent algorithms that enhance the predictive capabilities of our remote diagnostics platform used in railway signaling and other critical infrastructure. Responsibilities: Build and deploy machine learning and deep learning models for predictive maintenance and anomaly detection. Analyze time-series sensor data to develop accurate failure prediction models. Work with massive datasets – cleaning, preprocessing, feature engineering, and model tuning. Develop and expose ML models as REST APIs for integration into cloud-based systems. Collaborate with domain experts, data engineers, and full stack developers to create robust, production-grade solutions. Perform continuous evaluation and improvement of deployed models (MLOps). Stay updated with the latest AI research and evaluate them for real-world application. Required Skills & Qualifications: 2–5 years of experience in AI/ML project development and deployment. Proficiency in Python , Scikit-learn , Pandas , NumPy . Hands-on experience with TensorFlow or PyTorch . Solid understanding of ML algorithms , classification , regression , clustering , NLP , or computer vision . Experience with model deployment , APIs , and Docker . Knowledge of cloud platforms (AWS/GCP/Azure) is a plus. Strong problem-solving skills and understanding of statistical concepts. Nice to Have: Experience with time-series forecasting and anomaly detection. Prior exposure to predictive maintenance in industrial environments. Familiarity with IoT data and sensor networks.

Problem Definition: Partner with stakeholders to translate business goals into clear, data-focused questions and define project scope and success metrics. Data Collection and Preparation: Gather, clean, and preprocess data from diverse sources, ensuring quality and consistency, and engineer features to enhance model performance. Exploratory Data Analysis (EDA): Use statistical methods and visualization to uncover trends and validate assumptions, summarizing key insights for business alignment. Model Building and Evaluation: Select, train, and refine models suited to the business problem, evaluating performance with relevant metrics and documenting model assumptions. Deployment and Monitoring: Work with engineering teams to deploy models, establish performance monitoring, retrain as necessary, and incorporate feedback to improve accuracy. Requirements: Bachelor s/Master s in Data Science, Statistics, Computer Science, or related field. Experience in end to end model development to deployment and performance monitoring. Strong communication skills to convey insights to technical and non-technical audiences. Skills Needed: Strong knowledge of Applied AI ML & Deep Learning Data Science techniques, Hardcore in ANN /Deep Learning /Machine Learning/NLP Deep knowledge about machine learning algorithms such as tree-based methods, clustering, regression and classification, dimension reduction techniques, linear regression, Logistic regression, k-means, time series forecasting, Hypothesis testing (ANOVA, t-test, etc.), random forest, SVMs, Naive Bayes, gradient boosting, kNN, Deep learning algorithms like CNN, ANN and Reinforcement learning, Anomaly detection. In-depth understanding of Statistical concepts e.g. Probability distributions, statistical tests, correlation analysis, descriptive statistics, kernels, ROC, F1-Score etc. Advanced coding experience in at least one programming language (Python, Pyspark) & Strong experience in object-oriented concepts. Good to have advanced experience in one or more of the following: Spark, Databricks, Azure technical stack Good to have experience in model deployment to cloud/on-prem. Good Communication & presentation skills.

Description We are seeking an experienced GEN AIML Architect to lead the design and implementation of AI and ML solutions. The ideal candidate will have a strong background in AI/ML architecture, be able to innovate and enhance our AI capabilities, and work collaboratively with various teams to drive successful project outcomes. Responsibilities Design and develop advanced AI/ML architectures and frameworks. Collaborate with cross-functional teams to integrate AI solutions into existing systems. Conduct research and stay updated on the latest AI and ML technologies. Implement machine learning models and algorithms to solve real-world problems. Ensure data quality and integrity throughout the AI/ML development process. Provide technical guidance and mentorship to junior team members. Document architecture designs, processes, and best practices. Skills and Qualifications 10-15 years of experience in AI/ML architecture and design. Proficiency in programming languages such as Python, R, or Java. Strong understanding of machine learning algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience with data preprocessing, feature engineering, and model evaluation techniques. Knowledge of cloud platforms (AWS, Azure, GCP) and their AI/ML services. Familiarity with big data technologies such as Hadoop, Spark, or Kafka. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and teamwork skills to collaborate with stakeholders and clients.

Optum AI is UnitedHealth Groups enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform. Optum AI team members: Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone. Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development. Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the worlds top universities. OptumAI is looking for a Senior Machine Learning Engineer with deep subject matter expertise in text processing, NLU and SLU (Natural language understanding and Spoken Language Understanding) who will be part of a team leading the technical development and inventions that allow Optum machine learning products drive positive impact in the healthcare business. Your expertise will bring business and industry context to science and technology decisions. As part of the OptumAI AI/ML engineering group, you set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your code, designs and documents are exemplary and are used as references across the organization. A successful candidate is a hands-on AI/ML engineering expert that will tackle intrinsically hard problems, acquiring expertise as needed. The candidate will help decompose complex problems into straightforward solutions. Primary Responsibilities: Help design and develop the next generation of NLP, ML & AI products, and services for healthcare Develop machine learning and deep learning models and systems in domains including, but not limited to: NLP, NLU, NLG, SLU and multidimensional time series forecasting among others Exposure in RAG, LangChain, VectorDBs Ability to Quantize, Optimize GenAI models Manage NLP & ML models lifecycle for a suite of products Run large complex proof-of-concepts for the healthcare business Manage prioritization and technology work for building NLP, ML & AI solutions Lead the full end-to-end machine learning development process including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation Establish best practices for end-to-end deep learning and machine learning development cycle to ensure rigor in process and quality in outcome Work with a great deal of autonomy to find solutions to complex problems Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Graduate degree in applicable area of expertise or equivalent experience Experience in deploying scalable solutions to complex problems, from defining the problem, implementing the solution, and launching the new product successfully Skill Set; NLP, NLU, NLI Architecture: Transformers, Attention Models: GPT, Llama, Mistral Model Quantization Model Optimization Retrieval & Ranking, RAG, RAGAS Statistics, Machine Learning Models, Model Deployment Proven excellent communication, writing and presentation skills Experience in the health care industry Preferred Qualification: Experience in the health care industry

Description We are seeking an experienced NLP & LLM Engineer to join our team in India. The ideal candidate will be responsible for designing and implementing advanced NLP models and algorithms, as well as developing and fine-tuning large language models for various applications. This role requires a strong understanding of machine learning and natural language processing techniques, as well as the ability to collaborate with cross-functional teams to deliver innovative solutions. Responsibilities Design and implement natural language processing (NLP) models and algorithms. Develop and fine-tune large language models (LLMs) for various applications. Collaborate with data scientists and software engineers to integrate NLP solutions into products. Conduct research to improve the performance of existing NLP systems. Analyze and preprocess large datasets for training and evaluation of models. Stay updated with the latest advancements in NLP and machine learning technologies. Skills and Qualifications 3-8 years of experience in natural language processing and machine learning. Proficiency in programming languages such as Python, Java, or Scala. Experience with NLP libraries and frameworks such as NLTK, SpaCy, Hugging Face Transformers, or similar. Strong understanding of deep learning concepts and frameworks (e.g., TensorFlow, PyTorch). Familiarity with large language models (LLMs) and their applications. Solid background in statistics and data analysis. Ability to work with cloud platforms (AWS, GCP, Azure) for deploying NLP solutions. Excellent problem-solving skills and attention to detail.

Strong understating of Python, ML concepts and frameworks, Fast API, Graph QL Experience in developing scalable APIs. Knowledge of AWS, preferred services are storage, EC2, Kubernetes Exposure of ML best practices, documentation and unit testing. ML Flow, AirFlow, ML pipeline creation, drift monitoring and control Experience in developing and deploying machine learning models in a production environment using CI/CD. Communicate with clients to understand requirements and ask right questions. Knowledge of Django and database design will be added advantage. Strong analytical and problem-solving skills. Standards : Model Deployment Standards Use standardized APIs (e.g., RESTful) to interface with models Implement model versioning and proper naming conventions Monitoring and Maintenance Schedule routine model retraining and monitoring Code Quality Standards Follow style guides (e.g., PEP 8 in Python) Write comprehensive debugging and tests

We are seeking a Senior Python DevOps Engineer to develop Python services and build CI/CD pipelines for AI/data platforms. Must have strong cloud, container, and ML workflow deployment experience. Required Candidate profile Experienced Python DevOps engineer with expertise in CI/CD, cloud, and AI platforms. Skilled in Flask/FastAPI, Airflow, MLFlow, and model deployment on Dataiku and OpenShift.

We are seeking a skilled Machine Learning Engineer with experience in model development, versioning, and deployment, particularly in cloud environments. The candidate should have strong expertise in Natural Language Processing (NLP), text annotation, and information extraction. Key Responsibilities: Develop, version, and deploy machine learning models efficiently in cloud environments Work extensively with NLP techniques including text annotation and information extraction Collaborate with data scientists, engineers, and stakeholders to integrate ML solutions into products and workflows Optimize models for performance, scalability, and accuracy Document models, deployment processes, and workflows Required Skills: Proven experience with machine learning model lifecycle management including versioning and deployment Strong knowledge of cloud deployment platforms (AWS, Azure, GCP, etc.) Proficient in NLP techniques, text annotation, and information extraction Good problem-solving and communication skills

Description We are seeking a skilled AI/ML Engineer to join our team in India. The ideal candidate will have a strong background in machine learning and artificial intelligence, with the ability to develop and deploy innovative solutions that address complex problems. You will collaborate with cross-functional teams to create advanced AI models that enhance our product offerings. Responsibilities Design and implement machine learning models and algorithms. Collaborate with data scientists and software engineers to integrate AI solutions into applications. Analyze large datasets to derive insights and improve model performance. Conduct experiments to evaluate and optimize machine learning algorithms. Stay updated on the latest trends and advancements in AI and machine learning technologies. Skills and Qualifications Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Strong programming skills in Python, Java, or C++. Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch. Proficiency in data manipulation and analysis using libraries like Pandas and NumPy. Familiarity with SQL and database management systems. Knowledge of statistical analysis and data visualization tools. Understanding of algorithms, data structures, and software engineering principles.

Description We are seeking a Computer Vision Engineer to join our team in India. The ideal candidate will have a strong background in developing and implementing computer vision algorithms and models, with experience in machine learning and image processing. Responsibilities Develop and implement computer vision algorithms and models for various applications. Collaborate with cross-functional teams to integrate computer vision solutions into products. Analyze and interpret image data to improve the performance of existing models. Conduct research to stay updated on the latest advancements in computer vision technology. Optimize computer vision models for performance and scalability. Prepare and present reports on project progress and findings. Skills and Qualifications 2-6 years of experience in computer vision or related fields. Strong proficiency in programming languages such as Python and C++. Experience with computer vision libraries such as OpenCV, TensorFlow, or PyTorch. Solid understanding of machine learning algorithms and techniques. Familiarity with image processing techniques and tools. Knowledge of deep learning frameworks and neural networks. Strong analytical and problem-solving skills. Ability to work in a team environment and communicate effectively.

Description We are seeking an experienced AI/ML Engineer to join our dynamic team in India. The ideal candidate will have a strong background in developing machine learning models and algorithms, with a passion for leveraging data to drive business decisions. Responsibilities Design and implement machine learning models and algorithms to solve complex problems. Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications. Conduct data analysis and preprocessing to ensure high-quality input for models. Monitor and evaluate model performance, making improvements as necessary. Stay updated with the latest advancements in AI/ML technologies and methodologies. Document processes, code, and model performance for future reference and compliance. Skills and Qualifications 5-10 years of experience in AI/ML development and deployment. Proficient in programming languages such as Python, R, or Java. Strong understanding of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Experience with data manipulation and analysis libraries such as Pandas and NumPy. Knowledge of SQL and experience with database management. Familiarity with big data technologies like Hadoop or Spark is a plus. Ability to work with cloud platforms (AWS, Azure, Google Cloud) for deploying ML models. Excellent problem-solving skills and a keen analytical mindset.