Machine Learning Engineer

Title: Machine Learning Engineer Job Type: Full-Time Location: Remote Company Description: Mechanized AI is at the forefront of AI innovation, leveraging cutting-edge technology to transform legacy systems into modern, efficient, and scalable solutions. We work with enterprise clients to breathe life into their existing software, ensuring that they can meet the demands of today’s fast-paced, digital landscape. Our team thrives on solving complex challenges and delivering innovative solutions. As an organization, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning. Job Summary: We are seeking an experienced Machine Learning Engineer to join our growing team. The ideal candidate will have a background in Machine Learning (ML) with at least four years of experience outside of academia. They must be passionate about AI and stay up to date with the latest developments in the field. Key Responsibilities:

• Contribute to building and enhancing our Mechanized AI platform and AI-enabled products including mAI Modernize
• Serve as ML SME on client projects as needed
• Design ML systems
• Research and implement appropriate ML algorithms and tools
• Select appropriate datasets and data representation methods
• Run ML tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks
• Stay current with emerging technologies and ML best practices to continuously improve our methodologies and tools

• 4+ years of ML experience at a start-up or larger enterprise – high priority
• 6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI) applications – high priority
• Client delivery experience – high priority
• Effective written and oral communications skills (C1/C2 - advanced/proficient level English is required) – high priority
• Bachelor’s degree in computer science, software engineering or related field
• Experience with cloud environments (e.g., AWS, Azure, GCP)
• Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-learn)
• Experience developing, deploying, and managing/monitoring models
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture
• Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies
• Advanced experience in NLP techniques and applications
• Strong proficiency in Python programming
• Familiarity with prompt engineering approaches and best practices
• Knowledge of data structures, data modeling, and software architecture
• Strong analytical and problem-solving skills, with ability to propose innovative solutions and troubleshoot issues
• Ability to work independently and as part of a collaborative team in a fast-paced environment

• Agent development
• Data privacy
• Fine tuning LLMs
• LLM architecture and techniques for performance
• MLOps
• ML evaluation
• Model decay and data drift detection and handling
• Pulumi, Terraform and/or Cloud SDKs
• PySpark
• Quantization
• Retrieval-augmented generation (RAG) optimization
• Security
• Vector databases