1558 Sagemaker Jobs - Page 30

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! Platform Development and Evangelism: Build scalable AI platforms that are customer-facing. Evangelize the platform with customers and internal stakeholders. Ensure platform scalability, reliability, and performance to meet business needs.  Machine Learning Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining. Implement A/B testing of models. Design APIs for model inferencing at scale. Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. LLM Serving and GPU Architecture: Serve as an SME in LLM serving paradigms. Possess deep knowledge of GPU architectures. Expertise in distributed training and serving of large language models. Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. Model Fine-Tuning and Optimization: Demonstrate proven expertise in model fine-tuning and optimization techniques. Achieve better latencies and accuracies in model results. Reduce training and resource requirements for fine-tuning LLM and LVM models. LLM Models and Use Cases: Have extensive knowledge of different LLM models. Provide insights on the applicability of each model based on use cases. Proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. DevOps and LLMOps Proficiency: Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Skill Matrix LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery. Cloud Knowledge: AWS/Azure/GCP Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert Proficient in Python, SQL, Javascript Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

🔍 We’re Hiring: ML Ops Engineer (5+ Years Experience) 📍 Preferred Location: Gurgaon (Open to Pune & Bangalore if needed) 💼 Employment Type: Full-Time Are you passionate about deploying and automating ML pipelines at scale? We’re looking for a hands-on ML Ops Engineer to join our growing team and help operationalize machine learning in production environments. ✅ Key Responsibilities: • Develop, deploy, and automate end-to-end ML pipelines. • Work closely with Data Science and Engineering teams to productionize ML models. • Ensure robustness, scalability, and automation in ML workflows. 🧠 Technical Requirements: Cloud & DevOps (AWS): • Deep experience with AWS core services • Hands-on with EKS, ECS, ECR, SageMaker (Jobs, Model Registry, Batch Transform, HP Tuning) • Familiar with Step Functions, EventBridge, SNS/SQS ML Concepts & MLOps Tools: • Strong grasp of how ML code is deployed in production environments • Experience with MLflow for tracking and model management • Solid understanding of CI/CD for ML (build, test, and deploy ML pipelines efficiently) 📍 Location Flexibility: • Preferred: Gurgaon • Open to: Pune & Bangalore for the right candidate ⸻ If you’re ready to scale ML in real-world applications, apply now or refer a friend who fits the bill! Dan@therxcloud.com

About Gartner IT: Join a world-class team of skilled engineers who build creative digital solutions to support our colleagues and clients. We make a broad organizational impact by delivering cutting-edge technology solutions that power Gartner. Gartner IT values its culture of nonstop innovation, an outcome-driven approach to success, and the notion that great ideas can come from anyone on the team. About the role: Gartner is seeking a talented and passionate MLOps Engineer to join our growing team. In this role, you will be responsible for building Python and Spark-based ML solutions that ensure the reliability and efficiency of our machine learning systems in production. You will collaborate closely with data scientists to operationalize existing models and optimize our MLOps workflows. Your expertise in Python, Spark, model inferencing, and AWS services will be crucial in driving our data-driven initiatives. What you’ll do: Develop ML inferencing and data pipelines with AWS tools (S3, EMR, Glue, Athena). Deploy and optimize ML models on SageMaker and EKS Implement IaC with Terraform and CI/CD for seamless deployments. Ensure data quality, pipeline reliability, and performance. Collaborate with product manager, data scientists and engineers for smooth operations. Communicate technical insights clearly and support production troubleshooting. What you’ll need: Must have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 2-4 years of experience building data and MLOPS pipelines using Python and Spark. Strong proficiency in Python and Spark. Hands-on experience with a wide range of AWS services for Big Data and MLOps, including but not limited to S3, Glue, Athena, SageMaker, Lambda, Step Functions, EMR, Kinesis Experience with Docker; Kubernetes (EKS) experience is a significant plus. Experience with CloudFormation or Terraform for deploying and managing AWS resources. Strong problem-solving and analytical skills. Ability to work effectively within a agile environment. Don’t meet every single requirement? We encourage you to apply anyway. You might just be the right candidate for this, or other roles. Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work. What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com. Job Requisition ID:101289 By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence. Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser.

About Gartner IT: Join a world-class team of skilled engineers who build creative digital solutions to support our colleagues and clients. We make a broad organizational impact by delivering cutting-edge technology solutions that power Gartner. Gartner IT values its culture of nonstop innovation, an outcome-driven approach to success, and the notion that great ideas can come from anyone on the team. About the role: Gartner is seeking a talented and passionate MLOps Engineer to join our growing team. In this role, you will be responsible for building Python and Spark-based ML solutions that ensure the reliability and efficiency of our machine learning systems in production. You will collaborate closely with data scientists to operationalize existing models and optimize our MLOps workflows. Your expertise in Python, Spark, model inferencing, and AWS services will be crucial in driving our data-driven initiatives. What you’ll do: Develop ML inferencing and data pipelines with AWS tools (S3, EMR, Glue, Athena). Deploy and optimize ML models on SageMaker and EKS Implement IaC with Terraform and CI/CD for seamless deployments. Ensure data quality, pipeline reliability, and performance. Collaborate with product manager, data scientists and engineers for smooth operations. Communicate technical insights clearly and support production troubleshooting. What you’ll need: Must have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 2-4 years of experience building data and MLOPS pipelines using Python and Spark. Strong proficiency in Python and Spark. Hands-on experience with a wide range of AWS services for Big Data and MLOps, including but not limited to S3, Glue, Athena, SageMaker, Lambda, Step Functions, EMR, Kinesis Experience with Docker; Kubernetes (EKS) experience is a significant plus. Experience with CloudFormation or Terraform for deploying and managing AWS resources. Strong problem-solving and analytical skills. Ability to work effectively within a agile environment. Don’t meet every single requirement? We encourage you to apply anyway. You might just be the right candidate for this, or other roles. #LI-PM2 Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work . What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com . Job Requisition ID:101289 By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence. Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibility: 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: Graduation Degree Experience with cloud platforms, particularly AWS AI services (Bedrock, SageMaker) and/or Azure OpenAI ServiceProven experience in developing and deploying LLM-powered applications in production Experience with foundation models and generative AI platforms (e.g. OpenAI, Anthropic, open-source models) Experience in building RAG solutions with vector databases (e.g. pgvector, Pinecone, OpenSearch) Familiarity with MLOps practices (deployment, monitoring, model lifecycle) Good understanding of modern NLP techniques (e.g. transformers, embeddings, prompt engineering) Solid understanding with Machine Learning Frameworks and Libraries (e.g., PyTorch, scikit-learn, TensorFlow, MLflow, Keras, XGBoost) Proven solid programming skills in Python, PySpark Proven exposure to AI orchestration frameworks such as LangChain, LangGraph and others Proven excellent communication and collaboration skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

At The Institute of Clever Stuff (ICS), we don’t just solve problems—we revolutionise results. Our mission is to empower a new generation of Future Makers today, to revolutionise results and create a better tomorrow. Our vision is to pioneer a better future together. We are a consulting firm with a difference, powered by AI, driving world-leading results from data and change. We partner with visionary organisations to solve their toughest challenges, drive transformation, and deliver high-impact results. We combine a diverse network of data professionals, designers, software developers, and rebel consultants alongside our virtual AI consultant, fortu.ai, who combine human ingenuity with fortu.ai’s AI-powered intelligence to deliver smarter, faster and more effective results. Meet fortu.ai Used by some of the world’s leading organisations as a business question pipeline generator, ROI tracker, and innovation engine all in one. Trained on 400+ accelerators and 8 years of solving complex problems with global organisations. With fortu.ai, we’re disrupting a $300+ billion industry, turning traditional consulting on its head. Context of work: The client is a global energy company undergoing a significant transformation to support the energy transition. We work within their Customers & Products (C&P) division, serving both B2C and B2B customers across key markets such as the UK, US, Germany, Spain, and Poland. This business unit includes mobility (fuel and EV), convenience retail, and loyalty. Scope of the work: Client project to deliver: Data Pipeline Development: Building new pipelines for data models using AWS Glue and PySpark. Leading on end-to-end data pipeline creation and execution Data Pipeline Management: Deploying new features into core data models that require re-deployment of the pipeline through staging environments (dev, pre-prod, prod). Supporting regular refreshes of the data. Data Model Performance: Leading on finding opportunities to optimise and automate data ingestion, data refreshes, and data validation steps for the data models. Data Modelling: Supporting the team in building new data models and solutions, working closely with data scientists. Data Quality Assurance: Establish processes to monitor data pipelines for data loss, corruption, or duplication and take corrective action. Requirements: Capable and confident in data engineering concepts: designing data models, building data warehouses, automating data pipelines, and managing large datasets. Strong background in data modelling, creating relational data models, data warehousing and ETL processes. The ability to design, build and manage efficient and reliable data pipelines. Strong coding best practices, including version control. Experience working in agile sprint-based delivery environments. Experience working with customer and transactional data. Experience collaborating with a mixed team of permanent client colleagues and other partners and vendors – working with: Data Scientists, Data Engineers, Data Analysts, Software Engineers, UI/UX Designers and internal Subject Matter Experts. Experience delivering to a large enterprise of stakeholders. Core Technologies: SQL, Python, PySpark/Spark SQL, AWS (Redshift, Athena, Glue, Lambda, RDS), AWS Serverless Data Lake Framework (SDLF), SQL client software (e.g. Dbeaver), Bazel (automated testing), Git. Nice-to-have Technologies: Databricks, Amazon SageMaker, Jupyter Notebook, MLOps, ML model development, and ML engineering would be advantageous.

Date: 27 Jun 2025 Company: Qualitest Group Country/Region: IN Key Responsibilities Design, develop, and deploy ML models and AI solutions across various domains such as NLP, computer vision, recommendation systems, time-series forecasting, etc. Perform data preprocessing, feature engineering, and model training using frameworks like TensorFlow, PyTorch, Scikit-learn, or similar. Collaborate with cross-functional teams to understand business problems and translate them into AI/ML solutions. Optimize models for performance, scalability, and reliability in production environments. Integrate ML pipelines with production systems using tools like MLflow, Airflow, Docker, or Kubernetes. Conduct rigorous model evaluation using metrics and validation techniques. Stay up-to-date with state-of-the-art AI/ML research and apply findings to enhance existing systems. Mentor junior engineers and contribute to best practices in ML engineering. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 4–8 years of hands-on experience in machine learning, deep learning, or applied AI. Proficiency in Python and ML libraries/frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost). Experience with data wrangling tools (Pandas, NumPy) and SQL/NoSQL databases. Familiarity with cloud platforms (AWS, GCP, or Azure) and ML tools (SageMaker, Vertex AI, etc.). Solid understanding of model deployment, monitoring, and CI/CD pipelines. Strong problem-solving skills and the ability to communicate technical concepts clearly.

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU’LL BE DOING Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccer’s machine-learning algorithms and take them to market with partnerships with different organizations Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with customers and BI experts to build out reports and dashboards that are most useful to customers Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Define and execute on the roadmap Requirements Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 2+ years of experience in Data Science (healthcare experience will be a plus) Strong written and spoken communication skills Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. Good to have - knowledge of Sagemaker/Databricks Experience of containerizing models with Docker, Git, APIs, etc Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here’s What We Offer Generous Leave Benefits : Enjoy generous leave benefits of up to 40 days. Parental Leave : Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy : Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance : We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU’LL BE DOING Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccer’s machine-learning algorithms and take them to market with partnerships with different organizations Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with customers and BI experts to build out reports and dashboards that are most useful to customers Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Define and execute on the roadmap Requirements Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 2+ years of experience in Data Science (healthcare experience will be a plus) Strong written and spoken communication skills Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. Good to have - knowledge of Sagemaker/Databricks Experience of containerizing models with Docker, Git, APIs, etc Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here’s What We Offer Generous Leave Benefits : Enjoy generous leave benefits of up to 40 days. Parental Leave : Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy : Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance : We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

Software Engineer Senior Analyst - HIH - Evernorth Position Overview The Provider Technology Shared Services Engineering team is seeking a Software Engineer Senior Analyst for a Band 3 Contributor Career Track position. The Software Engineer Senior Analyst will play a critical role in system development within the broader Provider Technology Solutions and Engineering organization, significantly influencing Operations and Technology Product Management. This position will provide expertise in the engineering, design, installation and startup of automated systems, including a self-service onboarding kit that enables users to begin utilizing the solution within minutes. The solutions developed will be accessible to individuals with minimal technical skills and will require no additional coding, ensuring zero maintenance is needed. As a member of our team, you will operate within a high-performance, high-frequency enterprise technology environment. This role entails collaborating closely with IT management and staff to identify automated solutions that leverage existing resources with tailored configurations for each use case. The objective is to minimize redundancy in solutions while promoting an enterprise mindset focused on reusability and maintaining high standards, ultimately ensuring minimal future maintenance requirements. The Software Engineer Senior Analyst demonstrates significant creativity, foresight, and sound judgment in the conception, planning, and execution of initiatives. This role requires extensive professional knowledge and expertise to effectively advise functional leaders. Additionally, the Senior Analyst stays informed about the latest advancements in technology, including AI and machine learning, to enhance both existing and new automation solutions. These solutions are designed to optimize production costs while facilitating the addition or updating of features aimed at improving the overall software development lifecycle experiences. Responsibilities Provide comprehensive consultation to business unit and IT management, as well as personnel, regarding all facets of application development, testing and automation solutions across diverse development, financial, operational, and computing environments. Offers leadership and strategic vision in architectural design and AI/ML guidance for the team. Perform comprehensive research to identify and recommend the most efficient, cost-effective, and scalable AI/ML automation solutions applicable throughout the Software Development Life Cycle (SDLC). This includes areas such as test data generation, code generation, test case generation, test script generation, root cause analysis, predictive analysis, etc., with the aim of enhancing the overall SDLC from development to production support. Ensures that engineering solutions are aligned with the overall Technology strategy while addressing all application requirements. Demonstrate industry-leading technical abilities that enhance product quality and optimize day-to-day operations. Understand how changes impact work upstream and downstream including various back-end and front-end architectural modules. Enhance personnel effectiveness using heat matrices to prioritize Quality and Development Engineering resources on high-impact interfaces while identifying areas of lesser focus. Proactively monitor and manage the design of supported automation solutions, ensuring scalability, stability, flexibility, simplicity, performance, availability, security, and capacity. Develop and implement automation solutions to improve engineering and operational efficiency. Troubleshoot and optimize automated solutions and related artifacts to ensure seamless execution in CI/CD pipelines and on local machines, minimizing software and package dependencies or conflicts to reduce cycle time. Execute on a strategy to hand over the automation solutions to every Agile teams for adoption and use within their areas of focus, requiring zero maintenance and minimal effort for any enhancements without delving into coding. Encouraging and building automated processes wherever possible. Recognized internally as a subject matter expert. Qualifications Required Skills: Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). Basic understanding of implementing Prompt Engineering, Finetuning and RAG. Strong foundation and practical experience in programming languages, especially Python, within the context of AI/ML workflows, crucial for transitioning from traditional software development processes to optimized and innovative solutions that enhance market agility. Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices. Security Best Practices: understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. Cloud Services: Familiarity with cloud platforms like AWS / Google Cloud / Azure for deploying and managing applications and AI models. Required Experience & Education: A Bachelor's degree in Computer Science or a related field is required. 3 - 5 years of experience in Software Development, including 3 years of professional experience in AI and Machine Learning engineering. At least 2 years of experience in Agile methodologies is required. Familiarity with an onshore/offshore operational model is essential. Demonstrated experience in the architecture, design and development of large-scale enterprise application solutions is required. Desired Experience: Proficient in AI/ML practices and automation techniques. Experienced in programming languages and scripting, including Python, Shell, Bash, Groovy, Ansible and Docker. Providing coaching and guidance to team members. Location & Hours of Work < >Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate.Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH) Equal Opportunity Statement Evernorth is an Equal Opportunity Employer actively encouraging and supporting organization-wide involvement of staff in diversity, equity, and inclusion efforts to educate, inform and advance both internal practices and external work with diverse client populations. About Evernorth Health Services Evernorth Health Services, a division of The Cigna Group, creates pharmacy, care and benefit solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention and treatment of illness and disease more accessible to millions of people. Join us in driving growth and improving lives.

🚀 We're Hiring: Sr. Solution Architect – Cloud 📍 Location: Delhi & Hyderabad 🕐 Experience: 5+ years 🌐 Expertise: AWS, Cloud Architecture, Automation, Security Are you passionate about building scalable, secure, and cost-efficient cloud solutions? We're looking for a hands-on Senior Solution Architect to lead cloud design, strategy, and automation for mission-critical systems. What You’ll Do: ✅ Design secure, scalable AWS architectures (compute, storage, networking, data, AI/ML) ✅ Create detailed architecture docs, migration plans, and cost models ✅ Drive cloud strategy, CI/CD, and automation using Terraform, CloudFormation, Jenkins ✅ Implement cloud security best practices (IAM, VPC, encryption, compliance frameworks) ✅ Lead architecture reviews, RCA sessions, and major incident management ✅ Mentor junior engineers and guide cross-functional teams ✅ Work with cutting-edge tools – SageMaker, Redshift, EKS, GuardDuty, and more What We’re Looking For: 🔹 5+ years of hands-on cloud architecture experience 🔹 Deep AWS knowledge: EC2, EKS, RDS, S3, VPC, Lambda, etc. 🔹 Strong scripting and automation (Python, Bash, PowerShell) 🔹 Excellent troubleshooting on Windows/Linux 🔹 AWS Certified Solutions Architect – Associate (mandatory) 🔹 Professional or DevOps Pro cert preferred 🔹 Strong communication and leadership skills 🔹 Bonus: Familiarity with Azure, Puppet, Chef, ServiceNow 👉 Ready to design the future of cloud with us? 📩 Apply now or connect with us to learn more!

About Gartner IT Join a world-class team of skilled engineers who build creative digital solutions to support our colleagues and clients. We make a broad organizational impact by delivering cutting-edge technology solutions that power Gartner. Gartner IT values its culture of nonstop innovation, an outcome-driven approach to success, and the notion that great ideas can come from anyone on the team. About The Role Gartner is seeking a talented and passionate MLOps Engineer to join our growing team. In this role, you will be responsible for building Python and Spark-based ML solutions that ensure the reliability and efficiency of our machine learning systems in production. You will collaborate closely with data scientists to operationalize existing models and optimize our MLOps workflows. Your expertise in Python, Spark, model inferencing, and AWS services will be crucial in driving our data-driven initiatives. What You’ll Do Develop ML inferencing and data pipelines with AWS tools (S3, EMR, Glue, Athena). Deploy and optimize ML models on SageMaker and EKS Implement IaC with Terraform and CI/CD for seamless deployments. Ensure data quality, pipeline reliability, and performance. Collaborate with product manager, data scientists and engineers for smooth operations. Communicate technical insights clearly and support production troubleshooting. What You’ll Need Must have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 2-4 years of experience building data and MLOPS pipelines using Python and Spark. Strong proficiency in Python and Spark. Hands-on experience with a wide range of AWS services for Big Data and MLOps, including but not limited to S3, Glue, Athena, SageMaker, Lambda, Step Functions, EMR, Kinesis Experience with Docker; Kubernetes (EKS) experience is a significant plus. Experience with CloudFormation or Terraform for deploying and managing AWS resources. Strong problem-solving and analytical skills. Ability to work effectively within a agile environment. Don’t meet every single requirement? We encourage you to apply anyway. You might just be the right candidate for this, or other roles. Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work . What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com . Job Requisition ID:101289 By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence. Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser.

Job Summary We are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years. This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams. Key Responsibilities Technical Leadership & Architecture Design and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications. Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions. Lead full lifecycle development of AI/ML/GenAI solutions—from PoC to production—ensuring reliability and performance. Define and implement best practices for MLOps, DataOps, and DevOps on AWS. AI/ML & Generative AI Expertise Design Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan. Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications. Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines. Cloud & Infrastructure Management Architect event-driven, serverless, and microservices architectures for AI/ML applications. Ensure high availability, disaster recovery, and cost optimization in cloud deployments. Implement IAM, VPC, security best practices, and compliance. Team & Client Engagement Lead and mentor a team of ML engineers, Python Developer and Cloud Engineers. Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions. Conduct technical workshops, training sessions, and knowledge-sharing initiatives. Multi-Client & Business Strategy Manage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs. Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions. Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings. Key Skills & Technologies Cloud & DevOps AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK) Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito AI/ML & GenAI LLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, Llama ML Frameworks: TensorFlow, PyTorch, LangChain, Hugging Face Vector DBs: OpenSearch, Pinecone, FAISS RAG Pipelines, Prompt Engineering, Fine-tuning Software Architecture & Scalability Serverless & Microservices Architecture API Design & GraphQL Event-Driven Systems (SNS, SQS, EventBridge, Step Functions) Performance Optimization & Auto Scali

About the Role We’re looking for top-tier AI/ML Engineers with 6+ years of experience to join our fast-paced and innovative team. If you thrive at the intersection of GenAI, Machine Learning, MLOps, and application development, we want to hear from you. You’ll have the opportunity to work on high-impact GenAI applications and build scalable systems that solve real business problems. Key Responsibilities Design, develop, and deploy GenAI applications using techniques like RAG (Retrieval Augmented Generation), prompt engineering, model evaluation, and LLM integration. Architect and build production-grade Python applications using frameworks such as FastAPI or Flask. Implement gRPC services, event-driven systems (Kafka, PubSub), and CI/CD pipelines for scalable deployment. Collaborate with cross-functional teams to frame business problems as ML use-cases — regression, classification, ranking, forecasting, and anomaly detection. Own end-to-end ML pipeline development: data preprocessing, feature engineering, model training/inference, deployment, and monitoring. Work with tools such as Airflow, Dagster, SageMaker, and MLflow to operationalize and orchestrate pipelines. Ensure model evaluation, A/B testing, and hyperparameter tuning is done rigorously for production systems. Must-Have Skills Hands-on experience with GenAI/LLM-based applications – RAG, Evals, vector stores, embeddings. Strong backend engineering using Python, FastAPI/Flask, gRPC, and event-driven architectures. Experience with CI/CD, infrastructure, containerization, and cloud deployment (AWS, GCP, or Azure). Proficient in ML best practices: feature selection, hyperparameter tuning, A/B testing, model explainability. Proven experience in batch data pipelines and training/inference orchestration. Familiarity with tools like Airflow/Dagster, SageMaker, and data pipeline architecture.

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU'LL BE DOING ▶ Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. ▶ Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information ▶ Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. ▶ Define technical architecture to productize Innovaccer's machine-learning algorithms and take them to market with partnerships with different organizations ▶ Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. ▶ Work with customers and BI experts to build out reports and dashboards that are most useful to customers ▶ Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. ▶ Define and execute on the roadmap Requirements ▶ Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) ▶ 2+ years of experience in Data Science (healthcare experience will be a plus) ▶ Strong written and spoken communication skills ▶ Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) ▶ Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering ▶ Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. ▶ Good to have - knowledge of Sagemaker/Databricks ▶ Experience of containerizing models with Docker, Git, APIs, etc ▶ Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here's What We Offer Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU'LL BE DOING ▶ Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. ▶ Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information ▶ Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. ▶ Define technical architecture to productize Innovaccer's machine-learning algorithms and take them to market with partnerships with different organizations ▶ Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. ▶ Work with customers and BI experts to build out reports and dashboards that are most useful to customers ▶ Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. ▶ Define and execute on the roadmap Requirements ▶ Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) ▶ 2+ years of experience in Data Science (healthcare experience will be a plus) ▶ Strong written and spoken communication skills ▶ Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) ▶ Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering ▶ Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. ▶ Good to have - knowledge of Sagemaker/Databricks ▶ Experience of containerizing models with Docker, Git, APIs, etc ▶ Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here's What We Offer Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

Job Title: MLOps Engineer – AWS SageMaker & MLflow (Remote) Location: Fully Remote (India Preferred) Experience Level: 5+ Years Employment Type: Full-Time Company: KrtrimaIQ Cognitive Solutions i Job Summary: KrtrimaIQ Cognitive Solutions is looking for a Senior MLOps Engineer with deep expertise in AWS SageMaker, MLflow, and end-to-end machine learning lifecycle management. The ideal candidate will have hands-on experience in deploying and managing scalable ML solutions in production environments and a passion for building reliable MLOps systems. This is a fully remote opportunity offering flexibility and the chance to work on innovative AI/ML products for global enterprises. Key Responsibilities: Design, build, and maintain scalable and secure MLOps pipelines using AWS SageMaker and MLflow Automate ML model lifecycle: training, testing, tracking, versioning, and deployment to production Implement CI/CD pipelines and DevOps practices for ML infrastructure Ensure reproducibility, monitoring, and performance optimization of deployed models Collaborate closely with Data Scientists, Data Engineers, and DevOps teams to streamline workflows Contribute to MLOps research and explore new tools and frameworks in the production ML space Ensure compliance with best practices in cloud computing, software development, and data security Must-Have Qualifications: 5+ years of professional experience in Software Engineering or MLOps Expertise in AWS, specifically AWS SageMaker for building and deploying ML models Hands-on experience with MLflow for model tracking, versioning, and deployment Strong programming skills in Python (R, Scala, or Spark is a plus) Solid experience in production-grade development and infrastructure automation Strong problem-solving, analytical, and research skills Preferred Qualifications: Experience with AWS DataZone Familiarity with Docker, Kubernetes, Airflow, Terraform, or other orchestration tools Understanding of data versioning, feature stores, and ML monitoring tools Exposure to MLOps research and experimentation in startup/innovation environments What We Offer: 💻 100% Remote Work Flexibility 🌐 Exposure to enterprise-grade AI and MLOps use cases 🤝 Collaborative work culture focused on innovation and learning 🚀 Fast-paced startup-like environment with global project opportunities  #mlops #awssagemaker #mlflow #python #aws #docker #immediatejoiner #remotemode #ai/mlsolutions

Years of Experience: 10-13 Years old Location: Navi Mumbai (Locals or relocation candidate) Notice Period: Immediate joiner preferred or 30 days Max Budget: 60 LPA Job Description: We are looking for an experienced AI/ML Lead to spearhead the design, development, and deployment of intelligent solutions across cloud environments. The ideal candidate will have a strong background in deep learning, big data processing, and AI integrations, with proven experience in applying OCR and prompt engineering in real-world enterprise use cases. This role requires both technical depth and team leadership to deliver scalable, production-grade models and collaborate across business functions. Key Responsibilities: • Lead AI/ML solution design and delivery across cloud platforms (Azure ML, AWS SageMaker). • Build, train, and deploy advanced models using Deep Learning Frameworks like TensorFlow and PyTorch. • Apply OCR techniques (with CNNs) for document image understanding and automation. • Drive prompt engineering for AI integrations (e.g., Copilot, OpenAI, IBM Watson). • Optimize model pipelines for performance and scalability within Azure Synapse and cloud-based data warehouses. • Collaborate across departments to apply AI in business intelligence and enterprise data architecture use cases. • Manage and mentor a team of junior AI engineers and analysts. • Work on structured and unstructured data pipelines using tools like Databricks, Spark, and Dask. • Utilize and integrate Amazon EC2, ECR, S3, Redshift and manage model training and deployment in cloud environments. Must-Have Skills: • Azure ML, AWS (SageMaker, CodeGuru, EC2, ECR, S3) • OCR with CNN • Deep Learning: TensorFlow, PyTorch • Prompt Engineering with OpenAI/Copilot • Big Data: Databricks, Spark, Dask • Business Intelligence & AI Integrations • Team Leadership & Client Communication

About Oportun Oportun (Nasdaq: OPRT) is a mission-driven fintech that puts its 2.0 million members' financial goals within reach. With intelligent borrowing, savings, and budgeting capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $16.6 billion in responsible and affordable credit, saved its members more than $2.4 billion in interest and fees, and helped its members save an average of more than $1,800 annually. Oportun has been certified as a Community Development Financial Institution (CDFI) since 2009. WORKING AT OPORTUN Working at Oportun means enjoying a differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture where we all feel a sense of belonging and are encouraged to share our perspectives. This inclusive culture is directly connected to our organization's performance and ability to fulfill our mission of delivering affordable credit to those left out of the financial mainstream. We celebrate and nurture our inclusive culture through our employee resource groups. Company Overview At Oportun, we are on a mission to foster financial inclusion for all by providing affordable and responsible lending solutions to underserved communities. As a purpose-driven financial technology company, we believe in empowering our customers with access to responsible credit that can positively transform their lives. Our relentless commitment to innovation and data-driven practices has positioned us as a leader in the industry, and we are actively seeking exceptional individuals to join our team as Senior Software Engineer to play a critical role in driving positive change. Position overview We are seeking a highly skilled Platform Engineer with expertise in building self-serve platforms that combine real-time ML deployment and advanced data engineering capabilities. This role requires a blend of cloud-native platform engineering, data pipeline development, and deployment expertise. The ideal candidate will have a strong background in implementing data workflows, building platforms to enable self-serve for ML pipelines while enabling seamless deployments. Responsibilities Platform Engineering Design and build self-serve platforms that support real-time ML deployment and robust data engineering workflows. Create APIs and backend services using Python and FastAPI to manage and monitor ML workflows and data pipelines. Real-Time ML Deployment Implement platforms for real-time ML inference using tools like AWS SageMaker and Databricks. Enable model versioning, monitoring, and lifecycle management with observability tools such as New Relic. Data Engineering Build and optimise ETL/ELT pipelines for data preprocessing, transformation, and storage using PySpark and Pandas. Develop and manage feature stores to ensure consistent, high-quality data for ML model training and deployment. Design scalable, distributed data pipelines on platforms like AWS, integrating tools such as DynamoDB, PostgreSQL, MongoDB, and MariaDB. CI/CD and Automation Use CI/CD pipelines using Jenkins, GitHub Actions, and other tools for automated deployments and testing. Automate data validation and monitoring processes to ensure high-quality and consistent data workflows. Documentation and Collaboration Create and maintain detailed technical documentation, including high-level and low-level architecture designs. Collaborate with cross-functional teams to gather requirements and deliver solutions that align with business goals. Participate in Agile processes such as sprint planning, daily standups, and retrospectives using tools like Jira. Experience Required Qualifications 5-10 years experience in IT 5-8 years experience in platform backend engineering 1 year experience in DevOps & data engineering roles. Hands-on experience with real-time ML model deployment and data engineering workflows. Technical Skills Strong expertise in Python and experience with Pandas, PySpark, and FastAPI. Proficiency in container orchestration tools such as Kubernetes (K8s) and Docker. Advanced knowledge of AWS services like SageMaker, Lambda, DynamoDB, EC2, and S3. Proven experience building and optimizing distributed data pipelines using Databricks and PySpark. Solid understanding of databases such as MongoDB, DynamoDB, MariaDB, and PostgreSQL. Proficiency with CI/CD tools like Jenkins, GitHub Actions, and related automation frameworks. Hands-on experience with observability tools like New Relic for monitoring and troubleshooting. We are proud to be an Equal Opportunity Employer and consider all qualified applicants for employment opportunities without regard to race, age, color, religion, gender, national origin, disability, sexual orientation, veteran status or any other category protected by the laws or regulations in the locations where we operate. California applicants can find a copy of Oportun's CCPA Notice here: https://oportun.com/privacy/california-privacy-notice/. We will never request personal identifiable information (bank, credit card, etc.) before you are hired. We do not charge you for pre-employment fees such as background checks, training, or equipment. If you think you have been a victim of fraud by someone posing as us, please report your experience to the FBI’s Internet Crime Complaint Center (IC3).

Join us as a Machine Learning Engineer In this role, you’ll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms Day-to-day, you’ll make sure that models and algorithms work effectively in a production environment while promoting data literacy education with business stakeholders If you see opportunities where others see challenges, you’ll find that this solutions-driven role will be your chance to solve new problems and enjoy excellent career development What you’ll do Your daily responsibilities will include you collaborating with colleagues to design and develop advanced machine learning products which power our group for our customers. You’ll also codify and automate complex machine learning model productions, including pipeline optimisation. We’ll expect you to transform advanced data science prototypes and apply machine learning algorithms and tools. You’ll also plan, manage, and deliver larger or complex projects, involving a variety of colleagues and teams across our business. You’ll Also Be Responsible For Understanding the complex requirements and needs of business stakeholders, developing good relationships and how machine learning solutions can support our business strategy Working with colleagues to productionise machine learning models, including pipeline design and development and testing and deployment, so the original intent is carried over to production Creating frameworks to ensure robust monitoring of machine learning models within a production environment, making sure they deliver quality and performance Understanding and addressing any shortfalls, for instance, through retraining Leading direct reports and wider teams in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and Scrum outcomes The skills you’ll need To be successful in this role, you’ll need to have a good academic background in a STEM discipline, such as Mathematics, Physics, Engineering or Computer Science. You’ll also have the ability to use data to solve business problems, from hypotheses through to resolution. We’ll look to you to have experience of at least twelve years with machine learning on large datasets, as well as experience building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including git, TeamCity and CodeDeploy. You’ll Also Need A good understanding of machine learning approaches and algorithms such as supervised or unsupervised learning, deep learning, NLP with a strong focus on model development, deployment, and optimization Experience using Python with libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow or PyTorch An understanding of PySpark for distributed data processing and manipulation with AWS (Amazon Web Services) including EC2, S3, Lambda, SageMaker, and other cloud tools. Experience with data processing frameworks such as Apache Kafka, Apache Airflow and containerization technologies such as Docker and orchestration tools such as Kubernetes Experience of building GenAI solutions to automate workflows to improve productivity and efficiency

Minimum of (3+) years of experience in AI-based application development. Fine-tune pre-existing models to improve performance and accuracy. Experience with TensorFlow or PyTorch, Scikit-learn, or similar ML frameworks and familiarity with APIs like OpenAI or vertex AI Experience with NLP tools and libraries (e.g., NLTK, SpaCy, GPT, BERT). Implement frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluate and analyze RAG solution and Utilise the best-in-class LLM to define customer experience solutions (Fine tune Large Language models (LLM)). Architect and develop advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others. Strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Explore and implement cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Proficiency in Python with the ability to get hands-on with coding at a deep level. Develop and maintain APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational database (e.g., MongoDB or Cassandra) Enthusiasm for continuous learning and professional developement in AI and leated technologies. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Knowledge of cloud services like AWS, Google Cloud, or Azure. Proficiency with version control systems, especially Git. Familiarity with data pre-processing techniques and pipeline development for Al model training. Experience with deploying models using Docker, Kubernetes Experience with AWS Bedrock, and Sagemaker is a plus Strong problem-solving skills with the ability to translate complex business problems into Al solutions.

About the job We are seeking an experienced AI/NLP Engineer to join our team. The ideal candidate will have expertise in working with large language models and AI-based tools, strong analytical skills, and experience developing, testing, and refining AI-driven applications. Know your team (“Legacy Rewired, Engineering the Future”) At ValueMomentum’s Engineering Centre, we are a team of passionate engineers who thrive on tackling complex business challenges with innovative solutions while transforming the P&C insurance value chain. We achieve this through a strong engineering foundation and by continuously refining our processes, methodologies, tools, agile delivery teams, and core engineering archetypes. Our core expertise lies in six key areas: Cloud Engineering, Application Engineering, Data Engineering, Core Engineering, Quality Engineering, and Domain expertise. Relevant Experience should be more than 3 Years on the same Programming: Python, TensorFlow, PyTorch, Scikit-learn ✔ MLOps & Deployment: Docker, Kubernetes, MLflow, Airflow ✔ Cloud: AWS (SageMaker), GCP (Vertex AI), Azure ML ✔ Big Data: Spark, Kafka, Hadoop ✔ Databases: SQL, NoSQL, GraphDBs ✔ DevOps: CI/CD, GitHub Actions, Terraform ✔ Optimization: ONNX, TensorRT, Pruning & Quantization Feature - AI Engineer Focus - Building and deploying AI systems Responsibilities - Developing algorithms, deploying models, ensuring scalability Skills - Strong programming, AI frameworks, cloud computing Goal - Create AI-powered solutions

Job Title: MLOps Engineer – AWS SageMaker & MLflow (Remote) Location: Fully Remote (India Preferred) Experience Level: 5+ Years Employment Type: Full-Time Company: KrtrimaIQ Cognitive Solutions 📧 Apply at: nikhil.kumar@krtrimaiq.ai Job Summary: KrtrimaIQ Cognitive Solutions is looking for a Senior MLOps Engineer with deep expertise in AWS SageMaker , MLflow , and end-to-end machine learning lifecycle management . The ideal candidate will have hands-on experience in deploying and managing scalable ML solutions in production environments and a passion for building reliable MLOps systems. This is a fully remote opportunity offering flexibility and the chance to work on innovative AI/ML products for global enterprises. Key Responsibilities: Design, build, and maintain scalable and secure MLOps pipelines using AWS SageMaker and MLflow Automate ML model lifecycle: training, testing, tracking, versioning, and deployment to production Implement CI/CD pipelines and DevOps practices for ML infrastructure Ensure reproducibility, monitoring, and performance optimization of deployed models Collaborate closely with Data Scientists, Data Engineers, and DevOps teams to streamline workflows Contribute to MLOps research and explore new tools and frameworks in the production ML space Ensure compliance with best practices in cloud computing , software development , and data security Must-Have Qualifications: 5+ years of professional experience in Software Engineering or MLOps Expertise in AWS , specifically AWS SageMaker for building and deploying ML models Hands-on experience with MLflow for model tracking, versioning, and deployment Strong programming skills in Python (R, Scala, or Spark is a plus) Solid experience in production-grade development and infrastructure automation Strong problem-solving, analytical, and research skills Preferred Qualifications: Experience with AWS DataZone Familiarity with Docker , Kubernetes , Airflow , Terraform , or other orchestration tools Understanding of data versioning , feature stores , and ML monitoring tools Exposure to MLOps research and experimentation in startup/innovation environments What We Offer: 💻 100% Remote Work Flexibility 🌐 Exposure to enterprise-grade AI and MLOps use cases 🤝 Collaborative work culture focused on innovation and learning 🚀 Fast-paced startup-like environment with global project opportunities How to Apply: Send your updated CV to: nikhil.kumar@krtrimaiq.ai

Software Engineer – AI/ML/LLM/Data Science Company Overview: Entra Solutions (A BSI Financial Services company) is a FinTech company specialized in technology based financial solutions and services for the mortgage Industry. We are a people-focused, growth-oriented, innovative company and we're looking for people like you to make a positive change and join our team today! We are looking for an innovative Software Engineer – AI/ML/LLM/Data Science to design, develop, and deploy AI-driven solutions using Machine Learning, NLP, and Large Language Models (LLMs). The ideal candidate will work with Python to build and optimize retrieval-augmented generation (RAG) systems, LLM fine-tuning, and vector search technologies. You will develop scalable AI pipelines, ensuring high performance and seamless integration with cloud and on-prem environments. This role involves MLOps best practices, AI model optimization, and deployment of intelligent applications. WHAT YOU WILL DO: Develop, fine-tune, and deploy AI/ML models and LLM-based applications for real-world use cases. Build and optimize retrieval-augmented generation (RAG) systems using Vector Databases (e.g., ChromaDB, Pinecone, FAISS). Work on LLM fine-tuning, embeddings, and prompt engineering to enhance model performance. Develop end-to-end AI solutions with APIs using FastAPI, Flask, or similar frameworks. Build and maintain scalable data pipelines for training and inferencing AI models. Deploy and manage models using MLOps best practices on AWS or Azure. Optimize AI model performance for low-latency inference and scalability. Collaborate with cross-functional teams (Product, Engineering, Data Science) to integrate AI capabilities into applications. WHAT WE’RE LOOKING FOR: Must Have: Proficiency in Python – Strong hands-on experience in AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, LangChain, OpenAI APIs. Good to Have: Experience with LLM fine-tuning, embeddings, and transformers. Knowledge of NLP, vector search technologies (ChromaDB, Pinecone, FAISS, Milvus). Experience in building scalable AI models and data pipelines with Spark, Kafka, or Dask. Familiarity with MLOps tools (Docker, Kubernetes, CI/CD for AI models). Hands-on experience in cloud-based AI deployment (AWS Lambda, SageMaker, GCP Vertex AI, Azure ML). Knowledge of prompt engineering, GPT models, or knowledge graphs. WHAT’S IN IT FOR YOU? Competitive Salary & Full Benefits Package PTOs / Medical Insurance Exposure to cutting-edge AI/LLM projects in an innovative environment Career Growth Opportunities in AI/ML leadership Collaborative & AI-driven work culture EEO Statement We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.

Machine Learning Engineer (L1) Experience Required: 2-4 years As a Machine Learning Engineer at Spring, you’ll help bring data-driven intelligence into our products and operations. You’ll support the development and deployment of models and pipelines that power smarter decisions, more personalized experiences, and scalable automation. This is an opportunity to build hands-on experience in real-world ML and AI systems while collaborating with experienced engineers and data scientists. You’ll work on data processing, model training, and integration tasks — gaining exposure to the entire ML lifecycle, from experimentation to production deployment. You’ll learn how to balance model performance with system requirements, and how to structure your code for reliability, observability, and maintainability. You’ll use modern ML/AI tools such as scikit-learn, HuggingFace, and LLM APIs — and be encouraged to explore AI techniques that improve our workflows or unlock new product value. You’ll also be expected to help build and support automated data pipelines, inference services, and validation tools as part of your contributions. You’ll work closely with engineering, product, and business stakeholders to understand how models drive value. Over time, you’ll build the skills and judgment needed to identify impactful use cases, communicate technical trade-offs, and contribute to the broader evolution of ML at Spring. What You’ll Do Support model development and deployment across structured and unstructured data and AI use cases. Build and maintain automated pipelines for data processing, training, and inference. Use ML and AI tools (e.g., scikit-learn, LLM APIs) in day-to-day development. Collaborate with engineers, data scientists, and product teams to scope and deliver features. Participate in code reviews, testing, and monitoring practices. Integrate ML systems into customer-facing applications and internal tools. Identify differences in data distribution that could affect model performance in real-world applications. Stay up to date with developments in the machine learning industry. Tech Expectations Core Skills Curiosity, attention to detail, strong debugging skills, and eagerness to learn through feedback Solid foundation in statistics and data interpretation Strong understanding of data structures, algorithms, and software development best practices Exposure to data pipelines, model training and evaluation, or training workflows Languages Must Have: Python, SQL ML Algorithms Must Have: Traditional modeling techniques (e.g., tree models, Naive Bayes, logistic regression) Ensemble methods (e.g., XGBoost, Random Forest, CatBoost, LightGBM) ML Libraries / Frameworks Must Have: scikit-learn, Hugging Face, Statsmodels, Optuna Good to Have: SHAP, Pytest Data Processing / Manipulation Must Have: pandas, NumPy Data Visualization Must Have: Plotly, Matplotlib Version Control Must Have: Git Others – Good to Have AWS (e.g., EC2, SageMaker, Lambda) Docker Airflow MLflow Github Actions