AI/ML Solution Engineer

Apply Description As an AI/ML Engineer, you will play a key role in designing, building, and deploying AI-powered and machine learning solutions that help our clients solve complex problems and unlock new opportunities. You’ll collaborate with consultants, data engineers, and client stakeholders to bring advanced AI and ML capabilities into real-world applications — from prototypes and proof-of-concepts to enterprise-scale systems. Beyond technical execution, this role is about enabling client success, simplifying complexity, and helping teams work smarter with AI. Here's what you'll do: Prioritize Client Success Collaborate with clients to understand business needs and translate them into AI/ML-driven solutions. Build, fine-tune, and integrate AI/ML models (LLMs, NLP, computer vision, deep learning, traditional ML). Deliver applications that are reliable, intuitive, and built for long-term value. Get Comfortable Being Uncomfortable Navigate emerging and rapidly changing AI/ML technologies and tools. Adapt quickly, lead through change, and make confident decisions with limited information. Push boundaries by recommending modern approaches and innovations in AI/ML. Peel Back the Onion Ask the right questions to uncover root causes and deliver solutions that solve the real problem. Dig into data pipelines, model architectures, optimization techniques, and workflows that drive better outcomes. Explore new capabilities in deep learning frameworks, MLOps practices, and cloud platforms. Build to Last Architect scalable, maintainable AI/ML solutions that go beyond one-off experiments. Uphold security, data governance, and best practices in every deployment. Monitor model performance, retrain when necessary, and implement CI/CD pipelines for continuous improvement. Coach and guide other team members to elevate technical delivery and AI/ML literacy. Embrace Being Small & Mighty Be scrappy, stay hungry. Move fast, experiment, and adapt. Roll up your sleeves and get your hands dirty with coding, data processing, deployment, and optimization. Push through challenges with grit and a growth mindset. Help Others Be Great Work collaboratively across teams, combining diverse skills and perspectives to drive better outcomes. Translate technical AI/ML concepts into clear insights for non-technical stakeholders. Communicate complex data, models, and outcomes in a way that’s clear and actionable. Requirements Proficiency in Python (required); Java, JavaScript, SQL/NoSQL, and data processing tools (NumPy, Pandas, PySpark). Understanding of C++, R, Julia, Scala a plus. Proven experience building and deploying LLM applications, developing agentic workflows, and applying advanced prompting and fine-tuning strategies. Knowledge of ETL/ELT pipelines, familiarity with big data frameworks, data pipeline tools, SQL/NoSQL Hands-on experience with model development, training, deployment, and maintenance. Experinece with Scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face, and modern architectures (CNNs, RNNs, Transformers). Experience with CI/CD pipelines, experiment tracking, model monitoring, versioning, and building scalable ETL/data pipelines. Experience with AWS, Azure, GCP cloud infrastructures. Containerization and Automation (Docker, Kubernetes, Jenkins, GitHub Actions). Solid foundations in linear algebra, calculus, probability/statistics; familiarity with responsible AI practices, ethics, bias, and governance a plus. Excellent communication skills to engage both technical and non-technical stakeholders, with a collaborative, problem-solving mindset.