Staff Machine Learning Engineer

Join PagerDuty as a Staff Machine Learning Engineer to tackle complex problems, ...

Location

Canada , Toronto

Salary:

156000.00 - 232000.00 CAD / Year

PagerDuty

Expiration Date

Until further notice

Requirements

8+ years of experience building, designing, and evolving data architecture for large-scale systems
Excellent communication skills
Experience working with Product teams, ensuring and driving a timely delivery
Have a deep understanding of the trade-offs to be considered when designing and delivering machine learning solutions to production
Experience leading cross-team architecture discussions, building technical prototypes, and driving the adoption of best practices across diverse teams
Demonstrated experience with data engineering processes, working with unstructured data and cloud-based data infrastructures
Passionate about ML engineering and interested in driving discussions with stakeholders and executives

Job Responsibility

Build and improve the capabilities of the data platform that enable and accelerate the production of ML/AI-based solutions
Drive and define standards for AI/ML across the organization
Provide guidance, technical leadership, and mentoring to other members of the team
Mentor junior members and participate in scaling up the existing team
Proactively recommend improvements and new approaches addressing potential systemic pain points and technical debt
Anticipate technical demands on the data platform based on the organization’s roadmap and systematically drive the evolution of the architecture toward those ends
Develop a long-term plan for ML/AI investments

What we offer

Competitive salary
Comprehensive benefits package from day one
Flexible work arrangements
Company equity
ESPP (Employee Stock Purchase Program)
Retirement or pension plan
Generous paid vacation time
Paid holidays and sick leave
Dutonian Wellness Days & HibernationDuty - companywide paid days off in addition to PTO
Paid parental leave: 22 weeks for pregnant parent, 12 weeks for non-pregnant parent

Fulltime

Engineering Manager, AI Platform

Lead Airtable's AI Platform pod, which builds the foundational infrastructure an...

Location

United States , San Francisco; New York City

Salary:

240000.00 - 339900.00 USD / Year

Airtable

Expiration Date

Until further notice

Requirements

Platform builder at heart: think in systems and abstractions
experience building infrastructure other teams depend on
Technical depth with strategic thinking
Systems thinker with shipping velocity
AI infrastructure experience: worked on ML platforms, agent frameworks, or AI infrastructure at scale
Quality through architecture
Strong technical and management growth trajectory: 5+ years experience as an engineer (previously in a staff or TL level IC position) and 1+ years as a manager, or a similar combination

Job Responsibility

Build the AI platform foundation: own the core agent architecture, orchestration layer, and runtime
Design for platform scale: create robust abstractions and APIs
Establish AI reliability systems: build evaluation frameworks, monitoring, and quality assurance systems
Drive technical strategy: partner with Staff+ engineers to define the technical roadmap
Enable AI democratization: build platform capabilities that make sophisticated AI accessible to all Airtable users

What we offer

Benefits
Restricted stock units
Incentive compensation

Fulltime

Sr. Staff ML Platform Engineer

Machine learning is the crucial enabler for every financial service that EarnIn ...

Location

United States , Mountain View

Salary:

360000.00 - 440000.00 USD / Year

EarnIn

Expiration Date

Until further notice

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field
8+ years of industry machine learning experience and excellent software engineering skills
Strong programming skills in Python, with familiarity in ML frameworks such as TensorFlow or PyTorch
Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI
Familiarity with data pipelines and workflow management tools
Strong communication and collaboration skills
Passion for learning and staying updated with the latest industry trends in machine learning and platform engineering

Job Responsibility

Design, build, and maintain a robust ML platform and tooling ecosystem that supports the entire machine learning lifecycle, from experimentation to production
Lead and mentor a team of ML engineers, deeply understanding their workflows to streamline model training, deployment, and monitoring, while ensuring reproducibility and consistency of results
Drive scalability, reliability, and cost efficiency of the ML platform, balancing performance with ease of use for scientists and engineers
Evaluate and adopt emerging technologies to continually advance the organization’s machine learning capabilities and maintain a competitive edge
Champion operational excellence, setting a high bar for engineering quality, reliability, and automation
Act as a catalyst for innovation, spearheading step-change improvements that unlock new opportunities for growth and efficiency

What we offer

equity and benefits

Fulltime