AI/ML Engineer - Adaptable Data Strategies
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New York City
United Kingdom
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CanadaJob Description
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We are obsessed with efficiency—allowing for real-time evolution of AI depends on making adaptable data and algorithms extremely efficient. The ideal candidate brings expertise in AI/ML, a strong track record of delivering impact, and cares about making an impact in the real world.
We’re looking for an engineer who thrives at the intersection of applied research and building real-world products. You’ll drive the design and implementation of adaptable data strategies. You’ll work directly with the founding team, contributing to both the research direction and the product vision. This role demands technical excellence and a passion for delivering real-world impact.
Responsibilities
Deliver Real-World Impact: Lead the development and deployment of efficient, adaptive ML systems in real production environments.
Hands-on Impact: The ideal candidate will own implementation of data products at Adaption. This position requires creativity and technical execution in addressing novel challenges related to data, interaction, and evaluation.
Qualifications
A Bachelor’s degree in Computer Science, Machine Learning, or a related field.
3-4 years of experience in machine learning, applied research, or systems-level engineering for AI.
Strong software engineering skills and familiarity with Python.
Exposure to working with observability tools in the past (e.g., OpenTelemetry, Docker, Grafana).
Excellent communication skills and ability to align technical work with high-level goals.
A mindset of ownership, curiosity, and a bias toward action.
Experience with online learning, reinforcement learning, or efficient ML architectures.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.
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Adaption Labs
View Company ProfileAdaption Labs is a premier, enterprise-grade AI research and development powerhouse engineered to orchestrate massive-scale adaptive-learning ecosystems and intelligent, frictionless continuous-interaction workflows. Operating as an "adaptability-first" innovation hub, the company eliminates the operational friction of traditional, legacy monolithic-AI models—which frequently suffer from static training-data, opaque update-cycles, and disconnected real-world feedback loops—by seamlessly deploying advanced gradient-free learning telemetry, rigorous dynamic-data optimization architectures, and cohesive cross-stack generative-interface frameworks. Moving beyond rigid legacy brute-force scaling paradigms, Adaption Labs empowers global startups and enterprises to dynamically synchronize their multilingual-application, vertical-AI, and real-time inference pipelines with elite, scalable, and audit-ready execution. Under the hood, their sophisticated proprietary operational infrastructure—bolstered by leadership from AI-research pioneers Sara Hooker and Sudip Roy—natively manages complex real-world signal ingestion, instantaneous on-the-fly model alignment, and compliance-hardened deployment workflows, providing the necessary operational foundation for the modern, AI-transformed intelligence economy. What sets Adaption Labs apart is its uncompromising dedication to frictionless "intelligence-that-evolves"; by bridging the gap between highly technical, performance-intensive real-time adaptation demands and accessible, high-velocity developer-centric interfaces, the firm empowers modern engineering organizations to radically accelerate their product-evolution velocity, eliminate systemic stagnation-bottlenecks, and build an unassailable foundation for continuous commercial and institutional dominance in the modern, AI-transformed global-technology landscape.
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