12 Ml Engineering Jobs

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

What You'll Do We are seeking an experienced Senior AI & Machine Learning Manager to lead our dynamic team in developing cutting-edge AI & ML solutions. This role is perfect for someone passionate about leveraging AI and ML, inspire creativity, and create impactful products. You will be responsible for our Generative AI systems and how we apply them at Avalara to simplify and scale tax compliance across our entire portfolio of products. Major initiatives currently involve creating conversational agents. As an integral part of our leadership team, you will have the opportunity to shape the future of our AI & ML initiatives, manage a talented team of AI professionals, and collaborate with cross-functional teams to implement strategic projects. This role will report to Sr Director of AI & ML. What Your Responsibilities Will Be Lead and manage a team of AI&ML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AI&ML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AI&ML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications: Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI & Machine Learning systems. Proficiency in programming languages relevant to AI & ML, such as Python, R, Java, Scala, C++ and familiarity with AI & ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI & ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing ETL pipelines and visualization tools. General Qualifications: Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI & ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies.

Role & responsibilities 3+ years of experience in Spark, Databricks, Hadoop, Data and ML Engineering. 3+ Years on experience in designing architectures using AWS cloud services & Databricks. Architecture, design and build Big Data Platform (Data Lake / Data Warehouse / Lake house) using Databricks services and integrating with wider AWS cloud services. Knowledge & experience in infrastructure as code and CI/CD pipeline to build and deploy data platform tech stack and solution. Hands-on spark experience in supporting and developing Data Engineering (ETL/ELT) and Machine learning (ML) solutions using Python, Spark, Scala or R languages. Distributed system fundamentals and optimising Spark distributed computing. Experience in setting up batch and streams data pipeline using Databricks DLT, jobs and streams. Understand the concepts and principles of data modelling, Database, tables and can produce, maintain, and update relevant data models across multiple subject areas. Design, build and test medium to complex or large-scale data pipelines (ETL/ELT) based on feeds from multiple systems using a range of different storage technologies and/or access methods, implement data quality validation and to create repeatable and reusable pipelines Experience in designing metadata repositories, understanding range of metadata tools and technologies to implement metadata repositories and working with metadata. Understand the concepts of build automation, implementing automation pipelines to build, test and deploy changes to higher environments. Define and execute test cases, scripts and understand the role of testing and how it works. Preferred candidate profile Big Data technologies Databricks, Spark, Hadoop, EMR or Hortonworks. Solid hands-on experience in programming languages Python, Spark, SQL, Spark SQL, Spark Streaming, Hive and Presto Experience in different Databricks components and API like notebooks, jobs, DLT, interactive and jobs cluster, SQL warehouse, policies, secrets, dbfs, Hive Metastore, Glue Metastore, Unity Catalog and ML Flow. Knowledge and experience in AWS Lambda, VPC, S3, EC2, API Gateway, IAM users, roles & policies, Cognito, Application Load Balancer, Glue, Redshift, Spectrum, Athena and Kinesis. Experience in using source control tools like git, bit bucket or AWS code commit and automation tools like Jenkins, AWS Code build and Code deploy. Hands-on experience in terraform and Databricks API to automate infrastructure stack. Experience in implementing CI/CD pipeline and ML Ops pipeline using Git, Git actions or Jenkins. Experience in delivering project artifacts like design documents, test cases, traceability matrix and low-level design documents. Build references architectures, how-tos, and demo applications for customers. Ready to complete certifications

Responsibilities Contribute to the industrialization of the ML & GenAI technical stacks of our AI Platform, by participating in their definition, architecture, development, test, documentation & maintenance phases. Ensure the development process of this stack follows the DevSecOps recommendations & best practices . Write ML pipelines to illustrate the AI Platform capabilities. Contribute to the CI/CD workflows developments to automate the integration and deployment of the various ML assets (code or models) into the different environments. Contribute to the definition of the LLMOps / MLOps operating model and make sure the AI Platform enforces this model. Collaborate with our internal stakeholders to co-design the new features of the AI Platform . Occasionally be embarked into one of our stakeholder teams to help them using the AI platform, write ML pipelines, and, in return, collect platform evolution needs. Occasionally contribute to the collective effort of run & support for the AI Platform. Qualifications Requirements and Skills 5+ years of experience in ML Engineering. Strong knowledge on Machine Learning (including ML model management context) and GenAI technologies (including RAG). Previous hands-on experience on MLOps or LLMOps disciplines is mandatory . Good knowledge of DevOps processes at scale and experience of production systems. Rigorous mindset (but still open to changes), oriented towards customers, problems solving & results. Good team player . Autonomous . Ideally, some knowledge of Energy Management and Automation market . At ease in an international work environment & fluent in English . Familiar with agile methodologies: Scrum, SAFe. Technologies: Azure and/or AWS cloud technologies and their respective ML platforms (AzureML, AWS SageMaker). Databricks. GitHub, Terraform. ML Tools such as MLFlow. GenAI & LLM tools

Role Overview We are seeking a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate has hands-on experience developing, fine-tuning, and deploying LLMs, alongside a deep understanding of the machine learning lifecycle. This role involves building scalable AI solutions, collaborating with cross-functional teams, and contributing to cutting-edge AI initiatives. Key Responsibilities Model Development & Optimization: Develop, fine-tune, and deploy LLMs like OpenAI's GPT, Anthropic's Claude, Googles Gemini, or AWS Bedrock. Customize pre-trained models for specific use cases, ensuring high performance and scalability. Machine Learning Pipeline Design: Build and maintain end-to-end ML pipelines, from data preprocessing to model deployment. Optimize training workflows for efficiency and accuracy. Integration & Deployment: Work closely with software engineering teams to integrate ML solutions into production environments. Ensure APIs and solutions are scalable and robust. Experimentation & Research: Experiment with new architectures, frameworks, and approaches to improve model performance. Stay updated with advancements in LLMs and generative AI technologies. Collaboration: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align ML solutions with business goals. Provide mentorship to junior team members as needed. Required Qualifications Experience: At least 5 years of professional experience in machine learning or AI development. Proven experience with LLMs and generative AI technologies. Technical Skills: Proficiency in Python (required) and basic knowledge of Java is needed Hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock. Familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face. Strong understanding of data structures, algorithms, and distributed systems. Cloud Expertise: Experience with AWS, GCP, or Azure, including services relevant to ML workloads (e.g., AWS SageMaker, Bedrock). Data Engineering: Proficiency in handling large-scale datasets and implementing data pipelines. Experience with ETL tools and platforms for efficient data preprocessing. Problem Solving: Strong analytical and problem-solving skills, with the ability to debug and resolve issues quickly. Preferred Qualifications Experience with multi-modal models and generative AI for images, text, or other modalities. Understanding of ML Ops principles and tools (e.g., MLflow, Kubeflow). Familiarity with reinforcement learning and its applications in AI. Knowledge of distributed training techniques and tools like Horovod or Ray. Advanced degree (Masters or Ph.D.) in Computer Science, Machine Learning, or a related field.

Position overview: We are seeking a ML Engineer with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Design, develop, and deploy machine learning systems, including Generative AI models and LLMs. Research and implement state-of-the-art ML algorithms and tools. Conduct data preprocessing, feature engineering, and statistical analysis. Train, fine-tune, and optimize machine learning models for performance and accuracy. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. Extend existing ML frameworks and libraries to meet project requirements. Stay updated with the latest advancements in machine learning and AI. Skills: Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. - must have Experience in handling databases (SQL and NoSQL) Exposure to MLFlow, KubeFlow, Git CI/CD Experience with containerization tools like Docker, and orchestration tools like Kubernetes Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding test

Position overview: We are seeking a ML Engineer with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Design, develop, and deploy machine learning systems, including Generative AI models and LLMs. Research and implement state-of-the-art ML algorithms and tools. Conduct data preprocessing, feature engineering, and statistical analysis. Train, fine-tune, and optimize machine learning models for performance and accuracy. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. Extend existing ML frameworks and libraries to meet project requirements. Stay updated with the latest advancements in machine learning and AI. Skills: Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. - must have Experience in handling databases (SQL and NoSQL) Exposure to MLFlow, KubeFlow, Git CI/CD Experience with containerization tools like Docker, and orchestration tools like Kubernetes Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding test

Develop AI/ML models and manage subsurface data quality to support exploration and production workflows. Ensure secure, ethical use of data and delivery of automated insights to business teams Required Candidate profile AI/data professionals with geoscience understanding, skilled in analytics, ML, and data pipelines, or geoscientists with experience in data governance, system integration, and workflow digitization

AI/ML Engineer for Medical Image processing Job description We are looking for an AI/ML Engineer to join our team and help integrate AI-driven image analysis into an existing medical imaging platform. This role involves developing or integrating AI models to analyze medical images (e.g., MRI brain scans for Alzheimers prediction). Key Responsibilities: Develop and optimize deep learning models (CNNs, Transfer Learning, TensorFlow, PyTorch) for medical image analysis. Work with medical imaging datasets (DICOM, NIfTI, etc.) to extract meaningful insights. Integrate AI models into the imaging platform and ensure seamless deployment. Required Skills: Strong expertise in Deep Learning (CNN, ANN, Transformers, TensorFlow, PyTorch, Keras). Experience with image processing libraries (OpenCV, MONAI, scikit-image). Proficiency in Python, SQL, and cloud-based AI deployment (AWS/GCP/Azure). Experience: 4 years in AI/ML with a focus on image analysis Industry: Healthcare AI / Medical Imaging If you are passionate about AI for medical imaging and want to work on cutting-edge healthcare AI solutions, wed love to hear from you! Apply now or DM me for more details! Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

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

What You'll Do We are seeking an experienced Senior AI Machine Learning Manager to lead our dynamic team in developing cutting-edge AI ML solutions. This role is perfect for someone passionate about leveraging AI and ML, inspire creativity, and create impactful products. You will be responsible for our Generative AI systems and how we apply them at Avalara to simplify and scale tax compliance across our entire portfolio of products. Major initiatives currently involve creating conversational agents. As an integral part of our leadership team, you will have the opportunity to shape the future of our AI ML initiatives, manage a talented team of AI professionals, and collaborate with cross-functional teams to implement strategic projects. This role will report to Sr Director of AI ML. What Your Responsibilities Will Be Lead and manage a team of AIML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AIML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AIML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI Machine Learning systems. Proficiency in programming languages relevant to AI ML, such as Python, R, Java, Scala, C++ and familiarity with AI ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing / ETL pipelines and visualization tools. General Qualifications Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies. This is a remote role.