ML Engineer

Summary

Join Human Agency as a Machine Learning Engineer and contribute to impactful AI projects across various industries. You will design, implement, and deploy scalable AI models and algorithms, develop robust data pipelines, and create APIs for seamless system integration. This role involves model fine-tuning, implementing MLOps best practices, and engaging in full-stack development using open-source libraries. You will collaborate with a passionate team in a collaborative and inclusive environment. The position offers competitive compensation, remote flexibility, and the opportunity to build AI solutions from the ground up.

Requirements

• Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Experience: 2+ years of experience in AI/ML development, with expertise in Generative AI and AI agents
• Technical Proficiency: Strong experience in Python, TensorFlow/PyTorch, and Hugging Face Transformers. Familiarity with LLMs (GPT, Claude, Gemini, etc.), vector databases, and retrieval-augmented generation (RAG)
• Knowledge Base: Strong understanding of NLP, deep learning, and model fine-tuning techniques. Knowledge of prompt engineering, reinforcement learning, and AI safety principles
• Development Methodologies: Experience with Lean/Agile development methodologies
• Project Lifecycle: Experience in project lifecycle activities on development and maintenance projects
• Soft Skills: Ability to work in a team in diverse/multiple stakeholder environments. Strong analytical and problem-solving skills
• Ability to travel when needed - as per job requirements

Responsibilities

• Deploy AI Solutions: Design and implement scalable AI models and algorithms that integrate seamlessly into enterprise systems, ensuring they meet business requirements and performance standards
• Develop Scalable Data Pipelines: Construct robust data pipelines to handle large-scale datasets efficiently, ensuring data integrity and accessibility for machine learning applications
• API Development and System Integration: Create and manage APIs to facilitate smooth interaction between AI models and other software components, ensuring cohesive system functionality
• Model Fine-Tuning: Continuously refine and optimize machine learning models to enhance performance and accuracy, adapting to evolving data patterns and business requirements
• Implement MLOps and DevOps Best Practices: Apply industry-standard practices in MLOps and DevOps to automate workflows, monitor model performance, and maintain system reliability and scalability
• Full-Stack Development: Engage in end-to-end development processes, from data preprocessing and model training to deployment and monitoring, ensuring a comprehensive approach to AI solution delivery
• Leverage Open-Source Libraries: Utilize and contribute to open-source machine learning libraries and frameworks to accelerate development and promote community collaboration

Preferred Qualifications

Additional Expertise: Experience with self-learning AI agents, autonomous workflows, or multi-agent systems. Background in graph-based AI, symbolic reasoning, or cognitive architectures. Contributions to open-source AI/ML projects or research publications in relevant domains

Benefits

• Work on impactful AI projects across industries
• Build AI solutions from the ground up with autonomy and ownership
• Competitive compensation and remote flexibility
• Collaborate with a team passionate about innovation and problem-solving