we are hiring a, high-agency ml/ai engineer to architect and deliver cutting-edge ai solutions for our enterprise clients. this isn't just another ml engineering role - you'll be the technical owner driving complex ai projects end-to-end, from ideation through production deployment and ongoing monitoring and improvement.
you'll spend your time:
- 50% building robust, scalable ai systems that solve real business problems
- 25% researching and prototyping innovative solutions using the latest ai advances
- 25% collaborating with clients and stakeholders to translate business needs into technical solutions
about thinkbridge
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 problems
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
our flagship policies and benefits:
- work from anywhere!
- flexible work hours
- all leaves taken are paid leaves
- family insurance
- quarterly collaboration week
