C the Signs

The Machine Learning Engineer will develop and deploy large language and machine learning models, focusing on data preprocessing, model training, and fine-tuning using healthcare datasets. This role involves collaboration with data scientists and clinicians to integrate models into production systems. | Candidates should have a Bachelor's or Master's degree in a relevant field and at least 5 years of experience in Machine Learning Engineering. Proficiency in Python and experience with large-scale data preprocessing and healthcare data are essential. | Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-tuning using large-scale healthcare datasets. This role requires a strong understanding of Large language models, machine learning principles, data engineering, and experience working with sensitive healthcare data. Key Responsibilities Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature engineering, and data normalization. Identify, collect, and curate relevant, industry-specific datasets for model retraining. Format data appropriately for the chosen LLM and training pipeline Model Training & Fine-Tuning: Design, train, and fine-tune various LLMs on extensive healthcare data to solve specific clinical or operational problems. Set up and manage the training environment, including GPU instances and required software. Train and fine-tune pre-trained LLMs on the custom dataset to achieve specific goals. Experiment with and fine-tune hyperparameters such as learning rate, batch size, and training epochs to optimize model performance. Integration of structured + unstructured data (multi-modal/multi-input models) Model Evaluation & Optimization: Evaluate model performance using appropriate metrics, identify areas for improvement, and implement optimization strategies. Pipeline Development: Develop and maintain robust and scalable data and ML pipelines for model training, inference, and deployment. Collaboration: Work closely with data scientists, clinicians, and software engineers to understand requirements, integrate models into production systems, and ensure data privacy and security compliance. Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions. Documentation: Maintain clear and comprehensive documentation of models, data pipelines, and experimental results. Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field. Experience: 5+ years of experience in Machine Learning Engineering or a similar role. Proven experience with large-scale data preprocessing, LLM/model training, and fine-tuning. Experience with distributed training (PyTorch Distributed, DeepSpeed, Ray, Hugging Face Accelerate). Experience with GPU/TPU optimization, memory management for large language models. Experience working with healthcare data is highly desirable. Technical Skills: Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong understanding of various machine learning algorithms,Large Language Models, and deep learning architectures. Experience with cloud platforms (e.g., GCP, AWS) and distributed computing frameworks (e.g., Spark) is a plus. Familiarity with MLOps practices and tools. Soft Skills: Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to work independently and as part of a team in a fast-paced environment. Why Join Us? Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact. Benefits: Competitive salary and benefits package. Flexible working arrangements (remote or hybrid options available). The opportunity to work on life-changing AI technology that directly impacts patient outcomes. Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity. Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

The Data Engineer will develop and fine-tune data for LLMs and machine learning models, managing the entire data lifecycle. Responsibilities include designing scalable data pipelines, ensuring data quality, and collaborating with data scientists and engineers. | Candidates should have a bachelor's degree in a related field and proven experience as a Data Engineer, particularly with big data technologies. Strong programming skills and experience with cloud services are essential. | Position Summary The Data Engineer will play a crucial role in developing and fine-tuning data specifically for our LLMs and machine learning models. This individual will be responsible for the entire data lifecycle, including gathering, cleaning, structuring, and optimizing large, diverse healthcare datasets. The ideal candidate will have a strong background in data engineering principles, experience with big data technologies, and a keen understanding of the unique challenges and requirements of healthcare data. You will design, build, and maintain scalable data pipelines that source, preprocess, and deliver high-quality, high-volume datasets to our machine learning engineers. This role requires a deep understanding of data engineering best practices coupled with specific knowledge of the data requirements for LLM training and refinement Key Responsibilities Collaborate with data scientists and machine learning engineers to understand data requirements for LLM and machine learning model fine-tuning. Design, build, and maintain scalable data pipelines to ingest, process, and store massive and diverse healthcare datasets. Implement robust data validation and monitoring to ensure the integrity, accuracy, and consistency of all training datasets. Implement robust data cleaning, validation, and transformation processes to ensure data quality and integrity. Develop and optimize data structures and schemas for efficient access and utilization by LLMs and machine learning models. Work with the team to identify and acquire new data sources, ensuring compliance with relevant healthcare regulations (e.g., HIPAA). Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability. Document data engineering processes, data models, and data dictionaries. Stay up-to-date with the latest advancements in data engineering, big data technologies, and machine learning. Required Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer, with a focus on big data technologies. Strong proficiency in programming languages such as Python, Scala, or Java. Extensive experience with data warehousing, ETL processes, and data modeling. Experience with major cloud providers (e.g., AWS, GCP, Azure) and their data storage and processing services. Hands-on experience with big data frameworks like Apache Spark for distributed processing. Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication and interpersonal skills. Preferred Master's degree in a related field. Experience with healthcare data and a good understanding of healthcare data standards (e.g., FHIR, HL7). Familiarity with machine learning concepts and LLM fine-tuning processes. Experience with data orchestration tools (e.g., Apache Airflow). Why Join Us? Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact. Benefits: Competitive salary and benefits package. Flexible working arrangements (remote or hybrid options available). The opportunity to work on life-changing AI technology that directly impacts patient outcomes. Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity. Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

Design and develop scalable backend microservices with architectural principles and collaborate cross-functionally to ensure production readiness and operational safety. | 8+ years backend experience with Java and microservices, Docker/container knowledge, domain-driven design expertise, and experience with deployment strategies and feature flagging. | We are looking for a thoughtful and experienced Senior Software Engineer to contribute to the design and development of resilient, scalable backend systems that power mission-critical enterprise applications. You’ll play a key role in shaping the architecture and delivery processes behind a modern, microservices ecosystem. This role is ideal for someone who thrives at the intersection of technical excellence and product impact; someone who doesn’t just ship code, but designs systems with long-term clarity, operational safety, and customer outcomes in mind. You’ll be responsible for applying architectural principles such as domain-driven design, enabling outageless deployments, and integrating practices like feature flagging and change isolation to support high-velocity, low-risk software delivery. You’ll work closely with cross-functional partners across engineering, product, and DevOps to ensure our services are well-structured, observable, and production-ready from day one. While the focus is backend, any experience with frontend technologies is a bonus; especially when collaborating on full-stack solutions. Technical Experience 8+ years of backend engineering experience, with deep expertise in Java and modern frameworks (e.g., Spring Boot, Micronaut, Quarkus). Proven success designing and maintaining microservices in production environments. Experience building event-driven systems and asynchronous communication patterns. Hands-on knowledge of Docker and containerized service development. Architecture & Delivery Expertise Strong foundation in domain-driven design (DDD) and modular system design. Demonstrated success implementing outageless deployments and release strategies like canary, progressive rollout, or blue/green. Experience implementing and managing change isolation using feature flag systems in production environments. Team & Product Mindset Product-focused mindset that can balance engineering quality with user impact and iterative delivery. Experience mentoring other engineers and driving alignment on architecture and delivery strategy. Skilled communicator who can break down technical decisions for stakeholders and lead through influence. Preferred Qualifications Experience with agentic systems and communication protocols is a plus Experience with cloud-native infrastructure and CI/CD in AWS, GCP, or Azure. Exposure to infrastructure-as-code tools like Terraform or Pulumi. Familiarity with observability platforms (e.g., Grafana, Prometheus, ELK). Effective in using AI powered code editors / IDE such as Cursor, Windsurf, etc Frontend experience (e.g., with React and TypeScript) is a plus Background in systems that support high availability, auditability, and compliance. Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Work From Home