Precognitas Health

Precognitas Health Pvt. Ltd., a fully owned subsidiary of Foresight Health Solutions LLC, is seeking a Data Engineer to build and optimize our data pipelines, processing frameworks, and analytics infrastructure that power critical healthcare insights. Are you a bright, energetic, and skilled data engineer who wants to make a meaningful impact in a dynamic environment? Do you enjoy designing and implementing scalable data architectures, ML pipelines, automating ETL workflows, and working with cloud-native solutions to process large datasets efficiently? Are you passionate about transforming raw data into actionable insights that drive better healthcare outcomes? If so, join us! Youll play a crucial role in shaping our data strategy, optimizing data ingestion, and ensuring seamless data flow across our systems while leveraging the latest cloud and big data technologies. Required Skills & Experience : 4+ years of experience in data engineering, data pipelines, and ETL/ELT workflows. Strong Python programming skills with expertise in Python Programming, NumPy, Pandas, and data manipulation techniques. Hands-on experience with orchestration tools like Prefect, Apache Airflow, or AWS Step Functions for managing complex workflows. Proficiency in AWS services, including AWS Glue, AWS Batch, S3, Lambda, RDS, Athena, and Redshift. Experience with Docker containerization and Kubernetes for scalable and efficient data processing. Strong understanding of data processing layers, batch and streaming data architectures, and analytics frameworks. Expertise in SQL and NoSQL databases, query optimization, and data modeling for structured and unstructured data. Familiarity with big data technologies like Apache Spark, Hadoop, or similar frameworks. Experience implementing data validation, quality checks, and observability for robust data pipelines. Strong knowledge of Infrastructure as Code (IaC) using Terraform or AWS CDK for managing cloud-based data infrastructure. Ability to work with distributed systems, event-driven architectures (Kafka, Kinesis), and scalable data storage solutions. Experience with CI/CD for data workflows, including version control (Git), automated testing, and deployment pipelines. Knowledge of data security, encryption, and access control best practices in cloud environments. Strong problem-solving skills and ability to collaborate with cross-functional teams, including data scientists and software engineers. Compensation will be commensurate with experience. If you are interested, please send your application to jobs@precognitas.com. For more information about our work, visit www.caliper.care

Machine Learning Engineer About Caliper: Caliper is an AI-enabled, comprehensive value-based care (VBC) risk analytics suite designed to provide affordable, accessible and actionable insights. Our solution empowers Community Care Providers to thrive in the VBC landscape, ensuring improved patient outcomes, operational efficiency and financial success. Position: Machine Learning Engineer (with NLP & AWS Experience) We are hiring a Machine Learning Engineer who brings strong foundational skills across ML workflows, with a working focus on Natural Language Processing (NLP) and experience deploying ML systems on AWS. This role is ideal for someone who is technically versatilecomfortable working across diverse machine learning problems including NLP, classification, forecasting, embeddings, and recommender systemswhile being hands-on with modern ML tooling, model lifecycle management, and cloud infrastructure. Key Responsibilities: Build and deploy ML models for a variety of use cases such as classification, prediction, NLP tasks, and recommender systems. Design, implement, and maintain end-to-end ML pipelines, including data preprocessing, model training, validation, and deployment. Apply NLP techniques where applicable (e.g., sentiment analysis, NER, document parsing, embeddings). Leverage AWS services (e.g., SageMaker, Lambda, S3, Bedrock, Comprehend) to deploy and scale ML solutions in production. Participate in model evaluation, monitoring, and retraining workflows. Collaborate with product, data, and engineering teams to understand requirements and translate them into ML-driven solutions. Support both experimental research and production-grade deployment workstreams. Required Skills & Experience: 4+ years of experience as a Machine Learning Engineer or Applied Scientist. Strong hands-on experience in core ML techniques: regression, classification, clustering, tree-based models, embeddings, etc. Solid Python programming skills and experience with libraries like Scikit-learn, PyTorch or TensorFlow, Pandas, NumPy. Exposure to NLP models and libraries (e.g., Hugging Face Transformers, spaCy, NLTK) with practical application experience. Experience deploying models using AWS cloud infrastructure, particularly SageMaker, Comprehend, Lambda, or Bedrock. Comfortable with model evaluation, metrics (e.g., accuracy, ROC-AUC, F1), and debugging pipelines in production. Experience working with version control, CI/CD tools, and basic MLOps practices. Nice to Have: Familiarity with Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., FAISS, Milvus, Weaviate). Knowledge of prompt engineering or foundation model tuning (e.g., OpenAI, Claude, Bedrock). Experience with time series models, anomaly detection, or customer intelligence use cases. Exposure to Docker, Kubernetes, or Airflow for workflow orchestration. What We are Looking For: A generalist ML engineer who can adapt to evolving problem statements across NLP, tabular, or other ML use cases. Someone who balances code quality and experimentation, and can own model delivery end-to-end. A collaborative team player who is curious, self-driven, and excited to build in a fast-paced environment. Compensation will be commensurate with experience. If you are interested, please send your application to jobs@precognitas.com and For more information about our work, visit www.caliper.care

Technical Product Manager Job Description: We are seeking a highly motivated and detail-oriented Technical Product Manager to lead the development and delivery of our cutting-edge technology products. You will work at the intersection of business, technology, and user experience, driving the product roadmap while collaborating with cross-functional teams, including engineering, design, marketing, and stakeholders. The ideal candidate is passionate about building innovative solutions, has strong technical expertise, and excels at translating complex technical concepts into actionable strategies. Key Responsibilities: Technical Expertise : Write detailed product specifications and user stories for development teams. Evaluate technical solutions and architectures to ensure scalability, performance, and reliability. Stay informed about emerging technologies and industry trends to identify opportunities for innovation. Proficiency in Technical Concepts and Tools Programming Fundamentals : Understand basic coding principles, programming languages (e.g., Python, Java, JavaScript, C#), and modern frameworks (e.g., React, Angular, Node.js). APIs and Integrations : Understanding how APIs work, including concepts like RESTful APIs, GraphQL, and how different systems communicate with each other. System Architecture : Familiarity with microservices, serverless architectures, and monolithic systems to assess trade-offs and scalability. Cloud Infrastructure & DevOps: Understanding cloud services like AWS, Google Cloud, or Azure, including services for computing (EC2, Lambda), storage (S3, Cloud Storage), and databases (RDS, BigQuery). CI/CD Pipelines : Familiarity with DevOps practices such as continuous integration, continuous deployment, and tools like Jenkins, GitHub Actions, or CircleCI. Containerization and Orchestration : Basic knowledge of tools like Docker and Kubernetes for deploying and managing applications at scale. Database Concepts : Knowledge of relational databases (SQL, MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra) for understanding data storage and querying. Data Pipelines : Familiarity with how data flows through systems and basic knowledge of ETL (Extract, Transform, Load) processes. Analytics Tools : Ability to use tools like Tableau, Power BI as well as SQL querying for generating insights and analyzing user behavior. User Experience and Frontend Development Frontend Technologies : Basic understanding of how frontend technologies like HTML, CSS, JavaScript, and frontend frameworks (e.g., React, Angular) work. UX Principles : Awareness of usability best practices, wireframing tools (Figma, Adobe XD, Sketch), and responsive design. AI/ML Technology Strong Understanding of Software Development Processes Knowledge of Development Methodologies: Familiarity with Agile, Scrum, and Kanban workflows, as well as experience using tools like JIRA or Confluence to manage sprints and track progress. Development Lifecycle: Understanding how products move through the software development lifecycle (SDLC) from ideation to deployment and maintenance. Product Strategy & Roadmap : Define and maintain the product vision, strategy, and roadmap in alignment with business goals. Prioritize product features and improvements based on user needs, market research, and technical feasibility. Cross-functional Collaboration : Work closely with engineering teams to define technical requirements and ensure timely delivery of features. Collaborate with design and UX teams to create intuitive, user-friendly interfaces. Partner with marketing and business development to develop go-to-market strategies and communicate product value. Stakeholder Management : Act as the primary point of contact between technical teams and business units. Data-Driven Decision Making : Monitor key performance metrics to assess product performance and identify areas for improvement. Conduct A/B testing and analyze user feedback to refine features and optimize the product experience. Qualifications Required Skills & Experience Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent work experience). 10 years of experience in product management, with a focus on AI/ML products. Proven ability to translate business requirements into technical specifications. Strong understanding of technical skills listed above. Experience with Agile methodologies and tools such as JIRA, Confluence, Aha! or Trello. Preferred Skills Hands -on coding experience (e.g., Python, Java, JavaScript) or familiarity with modern frameworks. Experience in US healthcare. Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud). Familiarity with data analytics tools and practices (e.g., SQL, Tableau). Soft Skills Exceptional communication and presentation skills. Strong problem-solving abilities with a keen attention to detail. Ability to thrive in a fast-paced, dynamic environment. Collaborative mindset with the ability to influence and drive alignment across teams. Compensation will be commensurate with experience. If you are interested, please send your application to jobs@precognitas.com. For more information about our work, visit www.caliper.care

We are looking for a skilled Machine Learning Engineer with strong expertise in Natural Language Processing (NLP) and AWS cloud services to design, develop, and deploy scalable ML models and pipelines. You will play a key role in building innovative NLP solutions for classification, forecasting, and recommendation systems, leveraging cutting-edge technologies to drive data-driven decision-making in the US healthcare domain. Key Responsibilities: Design and deploy scalable machine learning models focused on NLP tasks, classification, forecasting, and recommender systems. Build robust, end-to-end ML pipelines encompassing data ingestion, feature engineering, model training, validation, and production deployment. Apply advanced NLP techniques including sentiment analysis, named entity recognition (NER), embeddings, and document parsing to extract actionable insights from healthcare data. Utilize AWS services such as SageMaker, Lambda, Comprehend, and Bedrock for model training, deployment, monitoring, and optimization. Collaborate effectively with cross-functional teams including data scientists, software engineers, and product managers to integrate ML solutions into existing products and workflows. Implement MLOps best practices for model versioning, automated evaluation, CI/CD pipelines, and continuous improvement of deployed models. Leverage Python and ML/NLP libraries including scikit-learn, PyTorch, Hugging Face Transformers, and spaCy for daily development tasks. Research and explore advanced NLP/ML techniques such as Retrieval-Augmented Generation (RAG) pipelines, foundation model fine-tuning, and vector search methods for next-generation solutions. Required Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or a related technical field. 6+ years of professional experience in machine learning, with a strong focus on NLP and AWS cloud services. Hands-on experience in designing and deploying production-grade ML models and pipelines. Strong programming skills in Python and familiarity with ML/NLP frameworks like PyTorch, Hugging Face, spaCy, scikit-learn. Proven experience with AWS ML ecosystem: SageMaker, Lambda, Comprehend, Bedrock, and related services. Solid understanding of MLOps principles including version control, model monitoring, and automated deployment. Experience working in the US healthcare domain is a plus. Excellent problem-solving skills and ability to work collaboratively in an agile environment. Preferred Skills: Familiarity with advanced NLP techniques such as RAG pipelines and foundation model tuning. Knowledge of vector databases and semantic search technologies. Experience with containerization (Docker, Kubernetes) and cloud infrastructure automation. Strong communication skills with the ability to translate complex technical concepts to non-technical stakeholders.