Senior Machine Learning Engineer
Company DescriptionSoftInWay, Inc. is an engineering solutions company recognized for its innovative software, engineering services, and educational offerings. The company is dedicated to providing cutting-edge solutions that advance the development and optimization of engineering designs, catering to a variety of industries. With a strong commitment to innovation and collaboration, SoftInWay fosters an environment for professionals to thrive and contribute to groundbreaking projects.Role DescriptionThis is a full-time, on-site role located in Burlington, MA, for a Senior Machine Learning Engineer. The selected candidate will be responsible for:Architecting the ML Solver Platform:Define modular architecture for data preprocessing, model execution, and post-processing.Establish clear API contracts between Python/TensorFlow and C# services.Design, develop, and implement advanced machine learning algorithms and models, focusing on pattern recognition and neural network applicationsProductionizing ML Workflows:Convert research code into robust, testable, and observable services.Implement CI/CD pipelines, automated testing, and reproducibility standards.Integration & Interoperability:Design REST/gRPC endpoints for cross-language communication.Ensure compatibility with C#/.NET services.Performance & Scalability:Optimize GPU/CPU utilization, batching strategies, and memory management.Plan for multi-model and multi-tenant scenarios.MLOps & Lifecycle Management:Implement model versioning, artifact registries, and deployment workflows.Set up monitoring, logging, and alerting for solver performance.Security & Compliance:Apply best practices for secrets management, dependency scanning, and secure artifact storage.Additional responsibilities include analyzing large datasets, developing and improving algorithms, and collaborating with cross-functional teams to address engineering challenges and deliver optimized solutions.Required Skills & ExperienceML Frameworks: Expert in TensorFlow (TF2/Keras), experience with ONNX Runtime for inference.Programming: Advanced Python for ML; strong understanding of packaging, type checking, and performance profiling.Architecture: Proven experience designing scalable ML systems for production.APIs: Proficiency in gRPC/Protobuf and REST for cross-language integration.MLOps: CI/CD pipelines, containerization (Docker/Kubernetes), model registries, reproducibility.Performance Optimization: GPU acceleration (CUDA/cuDNN), mixed precision, XLA, profiling.Observability: Metrics, tracing, structured logging, dashboards.Security: SBOM, image signing, role-based access, vulnerability scanning.QualificationsExpertise in Pattern Recognition and Neural NetworksStrong foundation in Computer Science and proficiency in developing scalable solutionsIn-depth knowledge of Statistics and advanced AlgorithmsExperience with tools and techniques relevant to machine learning and data analysisMaster's or PhD in Computer Science, Data Science, Engineering, or a related fieldProblem-solving skills and the ability to collaborate with interdisciplinary teamsPrior experience in the engineering, manufacturing, or industrial sector is a plus