AI / ML Engineer

We are seeking an innovative and results-oriented Mid-Level AI/ML Engineer to join our dynamic team. This role is crucial for transforming novel concepts into robust, production-ready AI solutions. The ideal candidate possesses a strong background in Machine Learning engineering, extensive experience with cutting-edge LLMs and cloud-based AI services, and a commitment to maintaining high-quality, responsible AI systems. Key Responsibilities Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving. LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems. Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock, to build scalable and efficient solutions. MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration. Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality. Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact. Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features. Required Qualifications Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field. Education: Master’s degree in Computer Science, Data Science, Engineering, or a quantitative field. Technical Proficiency: Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn). Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure). Deep understanding of the architecture and fine-tuning of Large Language Models. Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval). Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions. Preferred Qualifications Hands-on experience developing applications or services using Google's Gemini API or models. Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock. Experience in building and managing multi-step, reasoning-based Agentic AI systems. Prior experience in optimizing models for latency and cost efficiency in a production environment. Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract #J-18808-Ljbffr