Senior Machine Learning Engineer II - AI Special Projects
Instacart
Senior Machine Learning Engineer II - AI Special Projects
Job Description
Responsibilities
- Build the team vision: Partner with cross-functional leaders to define key business challenges and design AI-first solutions that unlock substantial value for customers and stakeholders.
- Drive hands-on execution: Lead the development of personalized content and recommendation systems by leveraging a mix of generative and traditional machine learning architectures to drive core business outcomes.
- Deploy AI systems at scale: Drive end-to-end software development, including building ML services, agentic workflows, managing experiment lifecycles, and deploying production-ready AI solutions at scale.
- Innovate: Stay at the cutting edge of AI innovation by conducting literature reviews and exploring novel paradigms in recommendation systems (RecSys). Identify opportunities for customization and apply these advancements to meet Instacart's unique needs.
- Elevate the team: Mentor and guide junior team members, fostering learning, engagement, and technical growth within the team.
Required Qualifications
- Expertise in Generative AI technologies, including prompt engineering, model fine-tuning, and familiarity with emerging AI trends and AIQA processes.
- Strong background in traditional machine learning and deep learning fundamentals, with hands-on experience building efficient models using frameworks like PyTorch or TensorFlow.
- Professional software development skills, including building data pipelines (SQL/Spark), managing CI/CD workflows, and deploying models into production environments.
- Product-focused mindset with a bias for action and proven ability to define and solve complex business problems through cross-functional collaboration.
- Exceptional communication skills, with the ability to influence stakeholders and translate technical insights into actionable business strategies.
- An innovation-driven mindset, rooted in curiosity and a passion for pushing the boundaries of applied AI.
Preferred Qualifications
- Experience building scalable ranking and recommendation systems.
- Application of ML models within an e-commerce environment.
- Cloud infrastructure expertise (e.g., AWS, GCP), particularly in managing large GPU workloads for training and inference.
- Demonstrated success as a technical leader, with the proven ability to guide teams toward strategic, high-impact outcomes.
- Technical influence evidenced by contributions to blogs, published papers, or industry thought leadership.
Required Skills
- Generative AI technologies (prompt engineering, model fine-tuning, AIQA)
- Traditional machine learning and deep learning
- PyTorch or TensorFlow
- Data pipelines (SQL/Spark)
- CI/CD workflows
- Model deployment to production
- Product-focused mindset
- Cross-functional collaboration
- Communication skills
- Scalable ranking and recommendation systems
- E-commerce ML applications
- Cloud infrastructure (AWS, GCP, GPU workloads)
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
Salary Range
$203000 - $225000 CAD
Locations
- Canada, Canada (Remote)
Salary
203,000 - 225,000 CAD / yearly
Skills Required
- Generative AI technologies (prompt engineering, model fine-tuning, AIQA)intermediate
- Traditional machine learning and deep learningintermediate
- PyTorch or TensorFlowintermediate
- Data pipelines (SQL/Spark)intermediate
- CI/CD workflowsintermediate
- Model deployment to productionintermediate
- Product-focused mindsetintermediate
- Cross-functional collaborationintermediate
- Communication skillsintermediate
- Scalable ranking and recommendation systemsintermediate
- E-commerce ML applicationsintermediate
- Cloud infrastructure (AWS, GCP, GPU workloads)intermediate
Required Qualifications
- Expertise in Generative AI technologies, including prompt engineering, model fine-tuning, and familiarity with emerging AI trends and AIQA processes. (experience)
- Strong background in traditional machine learning and deep learning fundamentals, with hands-on experience building efficient models using frameworks like PyTorch or TensorFlow. (experience)
- Professional software development skills, including building data pipelines (SQL/Spark), managing CI/CD workflows, and deploying models into production environments. (experience)
- Product-focused mindset with a bias for action and proven ability to define and solve complex business problems through cross-functional collaboration. (experience)
- Exceptional communication skills, with the ability to influence stakeholders and translate technical insights into actionable business strategies. (experience)
- An innovation-driven mindset, rooted in curiosity and a passion for pushing the boundaries of applied AI. (experience)
Preferred Qualifications
- Experience building scalable ranking and recommendation systems. (experience)
- Application of ML models within an e-commerce environment. (experience)
- Cloud infrastructure expertise (e.g., AWS, GCP), particularly in managing large GPU workloads for training and inference. (experience)
- Demonstrated success as a technical leader, with the proven ability to guide teams toward strategic, high-impact outcomes. (experience)
- Technical influence evidenced by contributions to blogs, published papers, or industry thought leadership. (experience)
Responsibilities
- Build the team vision: Partner with cross-functional leaders to define key business challenges and design AI-first solutions that unlock substantial value for customers and stakeholders.
- Drive hands-on execution: Lead the development of personalized content and recommendation systems by leveraging a mix of generative and traditional machine learning architectures to drive core business outcomes.
- Deploy AI systems at scale: Drive end-to-end software development, including building ML services, agentic workflows, managing experiment lifecycles, and deploying production-ready AI solutions at scale.
- Innovate: Stay at the cutting edge of AI innovation by conducting literature reviews and exploring novel paradigms in recommendation systems (RecSys). Identify opportunities for customization and apply these advancements to meet Instacart's unique needs.
- Elevate the team: Mentor and guide junior team members, fostering learning, engagement, and technical growth within the team.
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
Tags & Categories
Senior Machine Learning Engineer II - AI Special Projects
Instacart
Senior Machine Learning Engineer II - AI Special Projects
Job Description
Responsibilities
- Build the team vision: Partner with cross-functional leaders to define key business challenges and design AI-first solutions that unlock substantial value for customers and stakeholders.
- Drive hands-on execution: Lead the development of personalized content and recommendation systems by leveraging a mix of generative and traditional machine learning architectures to drive core business outcomes.
- Deploy AI systems at scale: Drive end-to-end software development, including building ML services, agentic workflows, managing experiment lifecycles, and deploying production-ready AI solutions at scale.
- Innovate: Stay at the cutting edge of AI innovation by conducting literature reviews and exploring novel paradigms in recommendation systems (RecSys). Identify opportunities for customization and apply these advancements to meet Instacart's unique needs.
- Elevate the team: Mentor and guide junior team members, fostering learning, engagement, and technical growth within the team.
Required Qualifications
- Expertise in Generative AI technologies, including prompt engineering, model fine-tuning, and familiarity with emerging AI trends and AIQA processes.
- Strong background in traditional machine learning and deep learning fundamentals, with hands-on experience building efficient models using frameworks like PyTorch or TensorFlow.
- Professional software development skills, including building data pipelines (SQL/Spark), managing CI/CD workflows, and deploying models into production environments.
- Product-focused mindset with a bias for action and proven ability to define and solve complex business problems through cross-functional collaboration.
- Exceptional communication skills, with the ability to influence stakeholders and translate technical insights into actionable business strategies.
- An innovation-driven mindset, rooted in curiosity and a passion for pushing the boundaries of applied AI.
Preferred Qualifications
- Experience building scalable ranking and recommendation systems.
- Application of ML models within an e-commerce environment.
- Cloud infrastructure expertise (e.g., AWS, GCP), particularly in managing large GPU workloads for training and inference.
- Demonstrated success as a technical leader, with the proven ability to guide teams toward strategic, high-impact outcomes.
- Technical influence evidenced by contributions to blogs, published papers, or industry thought leadership.
Required Skills
- Generative AI technologies (prompt engineering, model fine-tuning, AIQA)
- Traditional machine learning and deep learning
- PyTorch or TensorFlow
- Data pipelines (SQL/Spark)
- CI/CD workflows
- Model deployment to production
- Product-focused mindset
- Cross-functional collaboration
- Communication skills
- Scalable ranking and recommendation systems
- E-commerce ML applications
- Cloud infrastructure (AWS, GCP, GPU workloads)
Benefits
- Highly market-competitive compensation
- New hire equity grant as well as annual refresh grants
Salary Range
$203000 - $225000 CAD
Locations
- Canada, Canada (Remote)
Salary
203,000 - 225,000 CAD / yearly
Skills Required
- Generative AI technologies (prompt engineering, model fine-tuning, AIQA)intermediate
- Traditional machine learning and deep learningintermediate
- PyTorch or TensorFlowintermediate
- Data pipelines (SQL/Spark)intermediate
- CI/CD workflowsintermediate
- Model deployment to productionintermediate
- Product-focused mindsetintermediate
- Cross-functional collaborationintermediate
- Communication skillsintermediate
- Scalable ranking and recommendation systemsintermediate
- E-commerce ML applicationsintermediate
- Cloud infrastructure (AWS, GCP, GPU workloads)intermediate
Required Qualifications
- Expertise in Generative AI technologies, including prompt engineering, model fine-tuning, and familiarity with emerging AI trends and AIQA processes. (experience)
- Strong background in traditional machine learning and deep learning fundamentals, with hands-on experience building efficient models using frameworks like PyTorch or TensorFlow. (experience)
- Professional software development skills, including building data pipelines (SQL/Spark), managing CI/CD workflows, and deploying models into production environments. (experience)
- Product-focused mindset with a bias for action and proven ability to define and solve complex business problems through cross-functional collaboration. (experience)
- Exceptional communication skills, with the ability to influence stakeholders and translate technical insights into actionable business strategies. (experience)
- An innovation-driven mindset, rooted in curiosity and a passion for pushing the boundaries of applied AI. (experience)
Preferred Qualifications
- Experience building scalable ranking and recommendation systems. (experience)
- Application of ML models within an e-commerce environment. (experience)
- Cloud infrastructure expertise (e.g., AWS, GCP), particularly in managing large GPU workloads for training and inference. (experience)
- Demonstrated success as a technical leader, with the proven ability to guide teams toward strategic, high-impact outcomes. (experience)
- Technical influence evidenced by contributions to blogs, published papers, or industry thought leadership. (experience)
Responsibilities
- Build the team vision: Partner with cross-functional leaders to define key business challenges and design AI-first solutions that unlock substantial value for customers and stakeholders.
- Drive hands-on execution: Lead the development of personalized content and recommendation systems by leveraging a mix of generative and traditional machine learning architectures to drive core business outcomes.
- Deploy AI systems at scale: Drive end-to-end software development, including building ML services, agentic workflows, managing experiment lifecycles, and deploying production-ready AI solutions at scale.
- Innovate: Stay at the cutting edge of AI innovation by conducting literature reviews and exploring novel paradigms in recommendation systems (RecSys). Identify opportunities for customization and apply these advancements to meet Instacart's unique needs.
- Elevate the team: Mentor and guide junior team members, fostering learning, engagement, and technical growth within the team.
Benefits
- general: Highly market-competitive compensation
- general: New hire equity grant as well as annual refresh grants
Tags & Categories