What You’ll Do
As a Lead MLOps Engineer, you’ll own the design and evolution of our ML infrastructure—enabling fast, reliable, and secure experimentation, deployment, and monitoring of AI agents and LLMs in production. You’ll guide a small but high-impact team of DevOps and ML engineers, ensuring our platform achieves best-in-class reliability, scalability, and velocity.
You’ll work cross-functionally with data scientists, AI engineers, and product teams to bring the next generation of AI workflows—from fine-tuning to agent orchestration—to life.
- Architect and evolve InteractiveAI’s ML infrastructure, from data ingestion to model serving and continuous learning loops
- Design and implement scalable, cloud-agnostic runtimes (Kubernetes/GPU clusters) across on-prem, VPC, and hybrid deployments
- Build automation for end-to-end ML pipelines (data → fine-tuning → evaluation → deployment)
- Establish gold standards for reproducibility, observability, and model governance
- Partner with AI Engineers to optimize training/inference performance and cost
- Build internal tooling to accelerate AI product delivery and reduce time-to-deploy
- Implement robust monitoring, logging, and alerting frameworks for ML workloads
- Drive adoption of CI/CD best practices for ML and infrastructure code
- Mentor and grow a small team of MLOps engineers, fostering technical excellence and ownership
What We’re Looking For
We’re seeking a hands-on technical leader who combines deep MLOps expertise with a builder’s mindset—someone who thrives in fast-moving environments and can scale both systems and teams.
Minimum Requirements:- 5+ years of experience in DevOps, MLOps, or Infrastructure Engineering roles
- Proven track record deploying and maintaining ML workloads in production
- Strong expertise in containerization and orchestration (Docker, Kubernetes)
- Experience building CI/CD pipelines for ML models and infrastructure
- Proficiency with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation)
- Strong coding/scripting skills (Python, Bash, or similar)
- Experience with monitoring and observability tools (Prometheus, Grafana, ELK, etc.)
- Experience with at least one major cloud provider (AWS, GCP, or Azure)
- Strong understanding of ML lifecycle management (training, evaluation, deployment, monitoring)
Additional Requirements:- Experience with MLflow, Weights & Biases, or other model-tracking systems
- Understanding of fine-tuning workflows (LoRA, QLoRA, PEFT) and LLM serving
- Exposure to RAG systems, vector databases, and large-model inference optimization
- Experience implementing security and compliance practices (GDPR, ISO 27001, etc.)
- Prior experience leading technical teams or mentoring engineers
- Familiarity with distributed training and GPU cluster management is a plus
Interview Process
We keep our process focused and respectful of your time. Most candidates complete it in 2–3 weeks. Here’s what to expect:
- Intro Call – 30 minutes with our team to align on fit and expectations
- Technical Challenge – A practical MLOps design or automation task
- Technical Interview – Deep dive into systems architecture, automation, and ML infrastructure
- Leadership & Values Interview – Assess alignment with InteractiveAI’s culture and growth mindset
- Offer – Final conversation and offer
We’re building a team of builders — people who care about impact, quality, and growth.
If that’s you, let’s talk —
careers@interactive.ai
About us
InteractiveAI is a fast-growing startup on a mission to empower enterprises with fully managed AI agent lifecycles.
We are building the next generation of enterprise-AI solutions, delivering an end-to-end Agentic IDE alongside an extensible ecosystem of agentic resources and solutions.
Our platform allows companies to orchestrate, monitor, evaluate, deploy and improve AI agents—and soon fine-tune and own their own models.
We value autonomy, speed, and innovation, and we’re building a world-class team to match. Our squads are lean, focused, and execution-driven.
If you thrive in high-performance environments and want to be part of a company that rewards transformational outcomes, this is for you.
