Senior AI/ML Engineer
Senior · 5-8 years
Join Fastlab AI Technologies as a Senior AI/ML Engineer to build production-grade ML systems, deploy models at scale, and solve high-impact enterprise problems.
About the Role
As a Senior AI/ML Engineer at Fastlab AI Technologies, you will design, train, and deploy machine learning systems that operate reliably at enterprise scale. You will work across the ML lifecycle: discovery, data preparation, model development, evaluation, deployment, and monitoring.
You will collaborate with data engineers, backend engineers, and product teams to translate real business problems into measurable ML outcomes. The role combines deep technical execution with strong ownership and pragmatic decision-making.
If you enjoy building end-to-end ML products and optimizing systems for accuracy, latency, and reliability, this role is for you.
Responsibilities
- ✓ Build and deploy ML models for classification, forecasting, anomaly detection, and recommendation use cases.
- ✓ Design evaluation metrics and offline/online experimentation plans to validate model impact.
- ✓ Develop robust data pipelines and feature engineering workflows with reproducible training runs.
- ✓ Implement MLOps best practices: model versioning, CI/CD, monitoring, drift detection, and retraining triggers.
- ✓ Optimize inference systems for latency, throughput, and cost across cloud and container environments.
- ✓ Collaborate with stakeholders to define problem statements, success metrics, and delivery milestones.
- ✓ Write clear technical documentation and share best practices within the team.
- ✓ Mentor engineers and participate in peer reviews and design reviews.
Requirements
- • 5+ years of experience building applied ML systems in production environments.
- • Strong Python skills and working knowledge of core ML tooling (scikit-learn, PyTorch or TensorFlow).
- • Experience with ML system design, data pipelines, and model deployment.
- • Hands-on knowledge of cloud fundamentals (AWS/Azure/GCP) and containerization (Docker).
- • Understanding of model evaluation, bias/fairness basics, and monitoring for real-world systems.
- • Strong communication skills and ability to work in cross-functional teams.
Nice to Have
- + Experience with LLM applications (RAG, embeddings, vector databases).
- + Experience with streaming systems (Kafka) and real-time feature pipelines.
- + Familiarity with Kubernetes and infrastructure as code (Terraform).
What We Offer
Competitive Salary
Supportive benefits designed for long-term growth.
Health Insurance
Supportive benefits designed for long-term growth.
Flexible Hours
Supportive benefits designed for long-term growth.
Remote Options
Supportive benefits designed for long-term growth.
Learning Budget
Supportive benefits designed for long-term growth.
Conference Sponsorship
Supportive benefits designed for long-term growth.
Team Retreats
Supportive benefits designed for long-term growth.
Wellness Programs
Supportive benefits designed for long-term growth.