ML- AI Engineer

Job Description This is a remote position. About think bridge thinkbridge is how growth-stage companies can finally turn into tech disruptors. They get a new way there – with world-class technology strategy, development, maintenance, and data science all in one place. But solving technology problems like these involves a lot more than code. That’s why we encourage think’ers to spend 80% of their time thinking through solutions and 20% coding them. With an average client tenure of 4+ years, you won’t be hopping from project to project here – unless you want to. So, you really can get to know your clients and understand their challenges on a deeper level. At thinkbridge, you can expand your knowledge during work hours specifically reserved for learning. Or even transition to a completely different role in the organization. It’s all about challenging yourself while you challenge small thinking. thinkbridge is a place where you can: Think bigger – because you have the time, opportunity, and support it takes to dig deeper and tackle larger issues. Move faster – because you’ll be working with experienced, helpful teams who can guide you through challenges, quickly resolve issues, and show you new ways to get things done. Go further – because you have the opportunity to grow professionally, add new skills, and take on new responsibilities in an organization that takes a long-term view of every relationship. thinkbridge.. there’s a new way there. ™ Why This Role Is Different True Ownership : You'll be the technical architect making critical design decisions, not just implementing someone else's vision Production Focus : We need someone who's deployed models/systems AND kept them running - monitoring drift, handling failures, improving performance Diverse Projects : From GenAI applications (65%) to classical ML solutions (35%), across Retail, HRTech, Fintech, and Healthcare domains Technical Architecture: Design systems and guide implementation decisions without the overhead of formal people management What is expected of you? As part of the job, you will be required to Architect end-to-end ML/AI solutions that actually work in production Build and maintain production-grade systems with proper monitoring, alerting, and continuous improvement Make strategic technical decisions on approach, tools, and implementation Translate complex AI concepts into business value for clients Set technical direction for project teams through architecture and best practices Stay current with AI research and identify practical applications for client problem s If your beliefs resonate with these, you are looking at the right place! Accountability –Finish what you started Communication–Context aware, pro-active, and clean communication Outcome –High throughput Quality –High-Quality work and consistency Ownership –Go Beyond Requirements Must have technical skills Strong Python proficiency with production ML experience Hands-on experience deploying AND maintaining ML systems in production Experience with both GenAI (LLMs, RAG systems) and classical ML techniques Understanding of ML monitoring, drift detection, and model lifecycle management Cloud deployment experience (Azure knowledge helpful; AWS experience highly valued) Containerization and basic MLOps practices Good to have technical skills Experience fine-tuning open-source models to match/beat proprietary models Advanced MLOps (CI/CD for ML, A/B testing, feature stores) Published work (papers, blogs, open-source contributions) Experience with streaming/real-time ML systems What We're Really Looking for Beyond technical skills, we need someone who: Takes initiative and drives projects without waiting for instructions Has actually felt the pain of their own technical decisions in production Can explain "why this approach" to both engineers and business stakeholders Thinks critically about when to use (and when NOT to use) GenAI Has opinions about ML best practices based on real experience Benefits Work from anywhere! Flexible work hours All leaves taken are paid leaves Family Insurance Quarterly Collaboration Week