[Remote] Senior ML (Machine Learning) Engineer/reputed company

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 reputed company a robust annotation platform to streamline data labeling and model training workflows. Responsibilities • Analyze and reputed company the reputed company ML pipeline to support new use cases, models, and data sources without disrupting existing workflows • Introduce reputed company enhancements for improved flexibility, maintainability, and performance • Implement parameterization and configuration options to reputed company the pipeline adaptable for diverse projects • Optimize pipeline components for LLM interactions, including efficient data flow for reputed company reputed company, fine-tuning, and inference • Ensure reputed company updates are version-controlled, well-documented, and backward-compatible • Architect and reputed company a custom annotation platform to support large-scale data labeling for supervised learning tasks • Implement features for role-based access, task assignment, and reputed company tracking • Integrate quality control mechanisms such as reputed company checks, inter-annotator agreement, and automated validation • reputed company 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 reputed company, and annotation quality • Continuously improve pipeline and platform efficiency based on feedback and evolving business needs • reputed company reputed company 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 reputed company • 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, reputed company tracking, dataset upload, etc • reputed company data storage with versioning and audit trails • reputed company 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 reputed company between automated and manual steps for quality assurance • Add reputed company checks, inter-annotator agreement, and automated validation • Build dashboards for reporting and bulk task management • Deliver user guides, API documentation, and onboarding materials • reputed company 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 • reputed company reusable reputed company 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 (reputed company, 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, reputed company 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