[Remote] Senior ML (Machine Learning) Engineer/Lead

Note: The job is a remote job and is open to candidates in USA. Infinite Computer Solutions is a global leader in digital engineering and IT services, specializing in driving digital transformation for Fortune 1000 companies. They are seeking a highly skilled Machine Learning Engineer to enhance and scale their existing ML pipeline and develop a robust annotation platform to streamline data labeling and model training workflows. Responsibilities • Analyze and extend the current ML pipeline to support new use cases, models, and data sources without disrupting existing workflows • Introduce modular enhancements for improved flexibility, maintainability, and performance • Implement parameterization and configuration options to make the pipeline adaptable for diverse projects • Optimize pipeline components for LLM interactions, including efficient data flow for prompt generation, fine-tuning, and inference • Ensure all updates are version-controlled, well-documented, and backward-compatible • Architect and develop a custom annotation platform to support large-scale data labeling for supervised learning tasks • Implement features for role-based access, task assignment, and progress tracking • Integrate quality control mechanisms such as consensus checks, inter-annotator agreement, and automated validation • Enable scalable storage and retrieval of annotated datasets with versioning and audit trails • Provide APIs and integration points for seamless interaction with ML pipelines and data sources • Automate repetitive tasks such as data validation, model retraining, and performance monitoring • Optimize pipeline and annotation workflows for distributed processing and cloud scalability • Work closely with Data Scientists, Data Engineers, and Product Managers to standardize ML development and annotation practices • Establish best practices for CI/CD in ML, including automated testing and deployment of models and annotation tools • Implement robust monitoring systems for pipeline health, data drift, and annotation quality • Continuously improve pipeline and platform efficiency based on feedback and evolving business needs • Develop continuous evaluation pipelines for LLM-driven features using human and automated metrics • Conduct a market assessment of existing annotation tools (SageMaker, Encord, etc.) for feature fit, scalability, and cost • Compare against internal requirements for customization, integration, and security • Deliver a recommendation report outlining pros/cons, estimated effort, and ROI for build vs. buy • Document functional and technical requirements for annotation workflows, user roles, and quality control • Implement annotation workflows: task assignment, progress tracking, dataset upload, etc • Enable data storage with versioning and audit trails • Develop APIs for integration with ML pipeline • Integrate pre-annotation capabilities using ML models to auto-label data before human review • Provide confidence scoring to prioritize human validation where model predictions are uncertain • Ensure seamless handoff between automated and manual steps for quality assurance • Add consensus checks, inter-annotator agreement, and automated validation • Build dashboards for reporting and bulk task management • Deliver user guides, API documentation, and onboarding materials • Extend existing pipeline to support new data sources and preprocessing modules • Integrate annotation platform APIs for seamless data flow • Incorporate LLM fine-tuning and inference steps into the pipeline • Develop reusable prompt templates and evaluation frameworks • Optimize latency, accuracy, and cost for LLM interactions • Implement monitoring for LLM performance metrics Skills • 10+ Years of experience • Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch) • Experience with workflow orchestration tools (Temporal, Airflow, Prefect) • Knowledge of containerization and cloud platforms (Docker, Kubernetes, AWS/GCP/Azure) • Familiarity with data engineering principles and tools (SQL) • Understanding of MLOps practices and annotation workflows • Experience with large language models (LLMs), including evaluation and integration in production pipelines • Experience in enhancing existing ML pipelines and integrating new components • Experience in building annotation tools or integrating with existing platforms (e.g., SageMaker) • Background in integrating multimodal models • Knowledge of model governance, prompt evaluation, and responsible AI principles for LLMs • Background in UI/UX design for data labeling interfaces • Strong problem-solving skills and ability to work in cross-functional teams Company Overview • Next-Gen Business Technology Platformization™, AI and Product Engineering Services. It was founded in 2001, and is headquartered in Rockville, Maryland, USA, with a workforce of 10001+ employees. Its website is Company H1B Sponsorship • Infinite Computer Solutions has a track record of offering H1B sponsorships, with 410 in 2025, 333 in 2024, 378 in 2023, 316 in 2022, 389 in 2021, 496 in 2020. Please note that this does not guarantee sponsorship for this specific role. Apply tot his job