AI Scientist / Senior AI Scientist

Order.co

3h • Onsite

About The Position

We are hiring an AI Scientist or Senior AI Scientist to ship applied AI from problem definition through deployed production, with direct accountability for measurable business outcomes. This is an embedded role on a product engineering squad building customer-facing ordering and workflow capabilities. Final title and scope are set based on the experience and impact demonstrated in our interview process. Success at either level means iterative, low-cycle-time delivery that compounds into meaningful KPI movement. Scope grows through the magnitude and reach of impact, not through long delivery windows.

Near-term focus areas include:
Predictive ordering — ML and AI capabilities that improve how customers plan and place orders
Agentic copilots for workflow management — intelligent assistance embedded in core product workflows (technical direction weighted toward Senior AI Scientist hires)

You will be embedded day-to-day with a product/engineering squad while reporting into the data team.

Requirements

• Proven track record delivering AI/ML systems to production with measurable business outcomes.
• Deep familiarity with current LLM and agent technologies, including practical evaluation and failure-mode handling.
• Demonstrated ability to productionize complex models and model-adjacent systems with strong reliability and observability practices.
• Heavy, day-to-day use of AI-native engineering workflows (coding, framing/design, debugging, and code review) for at least the past 18 months.
• Working implementation proficiency across at least two technical ecosystems/cloud stacks (for example AWS and GCP).
• Strong quantitative foundation in experimentation, statistical reasoning, and model evaluation.
• Strong collaboration skills; can drive alignment and decisions under ambiguity.
• 5–7+ years in applied data science / machine learning roles with repeated production delivery (AI Scientist Level).
• Track record owning initiatives end-to-end—not only contributing to models owned by others (AI Scientist Level).
• Leadership-level influence within a cross-functional squad; improves team decision quality through technical rigor (AI Scientist Level).
• 8+ years in applied data science / machine learning roles with portfolio-level outcome ownership (Senior AI Scientist Level).
• Track record owning AI/ML initiatives from concept through production and measurable business impact at cross-team scope (Senior AI Scientist Level).
• Stakeholder leadership across product, data, engineering, and operations; can resolve prioritization under ambiguity (Senior AI Scientist Level).

Nice To Haves

• Experience implementing local/self-hosted AI solutions (for example self-managed agent infrastructure on-prem or in your own environment).
• Experience with retrieval systems, vector search, ranking/recommendation, or other production AI personalization workflows.
• Experience in e-commerce, B2B vendor management, financial products, or external systems integrations.
• Experience setting team-level standards for model governance, monitoring, and responsible AI practices (Senior AI Scientist additional).
• Experience mentoring senior ICs and shaping cross-team technical direction (Senior AI Scientist additional).

Responsibilities

• Lead end-to-end lifecycle execution: problem framing, experimentation, model/system design, production rollout, and post-launch optimization that incorporate HITL feedback.
• Be accountable for business outcomes (for example conversion, margin, operational efficiency, retention)—not model metrics alone.
• Translate ambiguous business goals into clear technical bets, delivery plans, and measurable success criteria.
• Ship iteratively with short feedback loops; deliver meaningful impact at each step.
• Own one or more high-leverage initiatives per quarter with clear KPI hypotheses and delivery accountability (AI Scientist).
• Balance model quality, operational constraints, and time-to-value on assigned bets (AI Scientist).
• Define rollout strategy, failure modes, and iterative improvement loops for systems you own (AI Scientist).
• Establish model-operations playbooks for incident response and performance degradation on owned systems (AI Scientist).
• Mentor junior scientists and influence technical standards within your initiative scope (AI Scientist).
• Own a portfolio of AI opportunities tied to company-priority KPIs across multiple teams (Senior AI Scientist).
• Identify and prioritize highest-leverage opportunities; build the execution path, not only execute assigned work (Senior AI Scientist).
• Lead architecture and operational patterns for scalable model delivery that others can reuse (Senior AI Scientist).
• Raise team standards through repeatable model-to-production patterns, implementation quality, and decision velocity (Senior AI Scientist).
• Mentor experienced ICs and align senior stakeholders on AI prioritization and sequencing (Senior AI Scientist).
• Identify high-leverage AI opportunities using business context, data diagnostics, and technical feasibility.
• Design practical AI/ML solutions (leveraging both deterministic and LLM/agent-based patterns where appropriate) with clear trade-offs on accuracy, latency, cost, and reliability.
• Build and productionize complex model systems with engineering-quality discipline: testing, observability, rollback/fallback strategy, human-in-the-loop integration, and incident readiness.
• Define evaluation frameworks that connect offline/online model quality to KPI impact and risk/accuracy controls.
• Partner closely with product, engineering, analytics, and operations to align scope, sequencing, and accountability.
• Drive hands-on delivery on predictive ordering capabilities from early production through optimization (AI Scientist).
• Work closely with a principal-level data scientist on architecture choices while owning execution velocity (AI Scientist).
• Set technical direction for agentic workflow / copilot capabilities in partnership with product and engineering leadership (Senior AI Scientist).
• Co-own prioritization and standards with product, engineering, and data leadership — not execution alone (Senior AI Scientist).
• Mentor scientists and technical peers on applied AI execution, production quality, and pragmatic delivery (Senior AI Scientist).

Benefits

• Launches two or more AI capabilities to production on predictive ordering with clear KPI hypotheses and measurable outcome movement (AI Scientist - first 6-9 months).
• Establishes reliable model-operations practices (testing, observability, incident playbooks) for owned systems (AI Scientist - first 6-9 months).
• Delivers iteratively with low cycle time; each release produces an evaluable business signal (AI Scientist - first 6-9 months).
• Builds effective working rhythm with principal-level data scientist partner and embedded product squad (AI Scientist - first 6-9 months).
• Launches AI capabilities across more than one initiatives with measurable KPI impact at company-priority scope (Senior AI Scientist - first 6-9 months).
• Establishes a repeatable, low-cycle-time model delivery pattern adopted by others on the team (Senior AI Scientist - first 6-9 months).
• Creates durable alignment across product, engineering, and data stakeholders on AI prioritization and execution (Senior AI Scientist - first 6-9 months).
• Defines technical trajectory for agentic workflow / copilot capabilities alongside predictive ordering (Senior AI Scientist - first 6-9 months).

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed