COMPANY A1
AI Engineering
MemberofTechnicalStaff,MachineLearning
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Member of Technical Staff, Machine Learning at COMPANY A1. Skills: Machine Learning, Production ML systems. Build ML components. Improve ML components”
What You'll Achieve.
ML models meet accuracy targets; ML models meet latency targets; ML models meet reliability targets; Production issues identified quickly; Production issues debugged effectively; Root causes addressed; Data pipelines robust; Data pipelines reproducible; Data pipelines maintainable; Training loops robust; Training loops reproducible; Training loops maintainable; Inference systems robust; Inference systems reproducible; Inference systems maintainable; Deliver reliable ML-powered features; Iterations driven by real-world signals; Iterations driven by measurable improvements
Industry & Context.
Debug model issues; Debug performance problems; Debug production incidents; Troubleshoot production incidents
What They're Looking For.
Must Have
Foundations in machine learning, Modern neural architectures, Hands-on experience training ML models, Hands-on experience fine-tuning ML models, Hands-on experience deploying ML models, Production-quality code writing, Learning new tools quickly
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Improve ML components
Understand model behavior
Maintain data pipelines
Debug performance problems
Debug production incidents
Ship improvements iteratively
Learn from user feedback
Work with senior ML engineers
Work with product teams
Work under production constraints
How You'll Work.
Team & Collaboration
Senior ML engineers; Product teams; Engineers; Product; Research teams
Full Job Description
COMPANY A1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. ROLE As a Member of Technical Staff, Machine Learning, you will build core ML components. You will work on real production systems from day one, learning how large-scale ML behaves outside of research settings. This role is for engineers who want to develop strong systems judgment by shipping, debugging, and iterating on real-world ML. FOCUS - Build and improve ML components across data, training, evaluation, and inference. - Fine-tune and adapt models as part of larger production systems. - Implement evaluation and testing to understand model behavior. - Help build and maintain data pipelines for real-world and synthetic data. - Debug model issues, performance problems, and production incidents. - Ship improvements iteratively and learn from real user feedback. - Work closely with senior ML engineers and product teams. - Work under real production constraints: latency, cost, reliability, and safety TECH STACK - Python - PyTorch / JAX - Production ML systems running on GPUs IDEAL EXPERIENCE - Strong foundations in machine learning and modern neural architectures. - Some hands-on experience training, fine-tuning, or deploying ML models. - Comfortable writing production-quality code and learning new tools quickly. - Curious, coachable, and eager to learn from real systems in production. - Able to work through ambiguity with guidance and grow ownership over time. - Bias toward shipping, iteration, and continuous improvement. OUTCOMES - ML models in production meet expected accuracy, latency, and reliability targets. - Production issues are identified q
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