On The Spot Development
About On The Spot
We bring startups and disruptive tech companies to the local market, offering engineers the opportunity to work on innovative, high-impact products. Join us and become a member of their R&D team while we take care of employment, HR support, a benefits package, and an enjoyable work environment.
About the role As a Head of AI Engineering, you will own the full AI lifecycle - from research to production - and leads the development of models that significantly impact funnel performance, ranking, bidding, and creative optimization. Translates business and product needs into actionable ML solutions.
Responsibilities
Lead the end-to-end AI roadmap — from problem definition and research to model development, deployment, and continuous iteration in production
Architect and own scalable ML systems powering ranking, bidding, prediction, and creative optimization workflows
Drive model performance improvements using rigorous experiment design, online/offline evaluation, and continuous monitoring
Translate product and business goals into clear ML strategies, identifying where automation, prediction, or optimization can create measurable impact
Collaborate cross-functionally with Product, Engineering, and Growth teams to define requirements, integrate models, and deliver features that directly affect funnel quality and ROI
Establish high technical standards for model reliability, inference latency, data quality, and observability across the AI stack
Mentor and guide ML engineers and researchers, fostering a culture of experimentation, ownership, and high-velocity delivery
Design and implement scalable data pipelines for feature engineering, real-time inference, and model monitoring
Oversee the deployment of new models ensuring reproducibility, versioning, CI/CD automation, and robust validation
Partner with leadership to define long-term AI strategy and ensure AI investments align with product vision and revenue goals
Requirements
5+ years experience in applied ML, including hands on model development and deployment
Deep understanding of the full ML lifecycle: data prep → feature engineering →training → evaluation → deployment → monitoring
Proven experience building and owning ML systems in production, not only research prototypes
Strong product intuition - ability to translate business problems into ML formulations
Experience working with tabular data, predictive models, and optimization systems
Strong engineering capabilities (Python, SQL, distributed systems concepts)
Experience leading ML projects end to end in a fast moving environment
Strong communication skills - ability to work with Product, Engineering, and Business teams
Nice to Have
Prior experience managing or mentoring ML researchers/engineers
Experience with ranking, recommendation systems, or decision optimization
Experience building inference microservices and ML infrastructure
Familiarity with experiment design (A/B, bandits, uplift modeling)
Background in AdTech, marketplace optimization, or bidding systems
Benefits
Work in a highly professional team. Informal and friendly atmosphere in the team
Paid vacation — 20 business days per year, 100% sick leave payment
Equipment provision
Partially compensated educational costs (for courses, certifications, professional events, etc.)
Legal and Accounting support in Poland
Ability to work from our comfortable office in Warsaw at Prosta 51
5 sick days per year
Medical insurance (after the end of the probationary period)
Flexible working hours – we care about you (!) and your output
English and Polish classes 2 times a week (online)
Bright and memorable corporate life: corporate parties, gifts to employees on significant dates
#J-18808-Ljbffr
About the role As a Head of AI Engineering, you will own the full AI lifecycle - from research to production - and leads the development of models that significantly impact funnel performance, ranking, bidding, and creative optimization. Translates business and product needs into actionable ML solutions.
Responsibilities
Lead the end-to-end AI roadmap — from problem definition and research to model development, deployment, and continuous iteration in production
Architect and own scalable ML systems powering ranking, bidding, prediction, and creative optimization workflows
Drive model performance improvements using rigorous experiment design, online/offline evaluation, and continuous monitoring
Translate product and business goals into clear ML strategies, identifying where automation, prediction, or optimization can create measurable impact
Collaborate cross-functionally with Product, Engineering, and Growth teams to define requirements, integrate models, and deliver features that directly affect funnel quality and ROI
Establish high technical standards for model reliability, inference latency, data quality, and observability across the AI stack
Mentor and guide ML engineers and researchers, fostering a culture of experimentation, ownership, and high-velocity delivery
Design and implement scalable data pipelines for feature engineering, real-time inference, and model monitoring
Oversee the deployment of new models ensuring reproducibility, versioning, CI/CD automation, and robust validation
Partner with leadership to define long-term AI strategy and ensure AI investments align with product vision and revenue goals
Requirements
5+ years experience in applied ML, including hands on model development and deployment
Deep understanding of the full ML lifecycle: data prep → feature engineering →training → evaluation → deployment → monitoring
Proven experience building and owning ML systems in production, not only research prototypes
Strong product intuition - ability to translate business problems into ML formulations
Experience working with tabular data, predictive models, and optimization systems
Strong engineering capabilities (Python, SQL, distributed systems concepts)
Experience leading ML projects end to end in a fast moving environment
Strong communication skills - ability to work with Product, Engineering, and Business teams
Nice to Have
Prior experience managing or mentoring ML researchers/engineers
Experience with ranking, recommendation systems, or decision optimization
Experience building inference microservices and ML infrastructure
Familiarity with experiment design (A/B, bandits, uplift modeling)
Background in AdTech, marketplace optimization, or bidding systems
Benefits
Work in a highly professional team. Informal and friendly atmosphere in the team
Paid vacation — 20 business days per year, 100% sick leave payment
Equipment provision
Partially compensated educational costs (for courses, certifications, professional events, etc.)
Legal and Accounting support in Poland
Ability to work from our comfortable office in Warsaw at Prosta 51
5 sick days per year
Medical insurance (after the end of the probationary period)
Flexible working hours – we care about you (!) and your output
English and Polish classes 2 times a week (online)
Bright and memorable corporate life: corporate parties, gifts to employees on significant dates
#J-18808-Ljbffr