Own the production platform end to end, including the backend services, AWS infrastructure, and the iOS and web app, with a primary focus on backend
Compensation
Competitive compensation (cash + equity)
Responsibilities
Own the production platform end to end, including the backend services, AWS infrastructure, and the iOS and web app, with a primary focus on backend
Get up to speed quickly on an existing codebase, document what you learn, and make deliberate decisions about what to keep, refactor, or replace
Scale the platform to support more manufacturers, protocols, and dedicated customer environments without compromising data isolation
Improve the reliability and accuracy of our LLM-powered features, including retrieval over customer documentation, voice interaction, and guardrails against incorrect or unsafe responses
Build and maintain privacy and security controls our customers depend on, such as tenant isolation, account deletion, audit trails, and data retention
Own the path from signed pilot to production rollout, standing up Dalus in customer environments, migrating content, building integrations, and running workshops with systems engineers.
Compensation
a salary in the range of $120-240k
Responsibilities
Stand up Dalus in customer environments (cloud or on‑prem)
Migrate Cameo, Rhapsody and DOORS content into Dalus
Fix issues in the AI copilot
Scope and build integrations to Windchill, Teamcenter, Polarion and Jira
Run hands‑on workshops with customer systems engineers
Forward Deployed Engineer to bring AI into real business operations for the IFS M&A Group, building and running applications, integrating AI platforms with enterprise systems, and delivering production AI solutions.
Compensation
Salary Range: $130,000 to $160,000 annually + bonus
Responsibilities
Deliver assigned AI projects and workstreams from discovery through design, build, deployment, verification, training and support
Support discovery with business and technical stakeholders to understand workflows, systems and desired outcomes
Analyse non-routine requirements, recommend practical solution designs and implement them as tested code
Prototype quickly to validate a use case
Build integrations that connect AI platforms to existing applications, APIs and data sources
Software Engineer in Global Video Engineering – Live team at NBCUniversal
Compensation
Salary range: $105,000 - $145,000
Responsibilities
Design, develop, and maintain high-performance software systems and features, primarily using Go, to support large-scale video streaming platforms such as Peacock and NOW/WOW.
Build and maintain live and linear video streaming pipelines using in-house and third-party tools, focusing on video encoding, packaging, and content delivery.
Support live events and linear channels, helping ensure reliable and high-quality streaming experiences.
Collaborate with Engineering Managers and Principal Engineers to develop solutions that improve video delivery and enhance audio and video quality.
Work closely with Site Reliability Engineering (SRE) teams to build reliable, scalable, and resilient services across multiple regions.
Requirements
Bachelor’s degree or equivalent in Computer Science, Information Technology, or related field
Support the delivery of the controls portion of the project, including system component development, controls software development, integration, verification, and validation.
Compensation
AVL provides a competitive compensation and benefits package to all direct hires. Specific benefit details and offer packages will be communicated during the interview and/or offer stage.
Responsibilities
Performs System Component Development, Controls Software Development, System Integration, and System Verification & Validation activity and other relevant engineering project work within project team as required.
Mentors less experienced Engineers in the field of Controls.
Works on specific phases or aspects of projects such as technical studies, preparation of specifications, development of electrified systems/components, technical plans, powertrain system and component testing, data analysis and validation.
Supports/ensures data quality and writes technical project reports.
Reviews project for compliance with engineering principles, company standards, and customer requirements, including opinions and interpretations.
Lead the design, development, integration, and validation of automotive audio control modules for current and future vehicles.
Compensation
This position is a range of salary grades 6-8 and ranges from $74,300-$166,200.
Responsibilities
Play a key role in the technical specification, design, development, and validation of high-performance automotive AM, FM, HD, SiriusXM and DAB tuners and audio controllers
Work closely with internal and external stakeholders, including hardware engineers, software developers, and suppliers, to integrate audio controller solutions seamlessly into vehicle systems
Manage a supplier through all aspects of the core design and release of the product
Perform initial audio system issue triage using CAN tools
Develop engineering documentation related to audio tuner and controller development
Requirements
Bachelor’s degree in Electrical/Electronic Engineering, Computer Science, Software Engineering, or a related field
Nice to have: Master’s degree in Electrical/Electronic Engineering, Computer Science, Software Engineering, or a related field
Nice to have: Passion for automotive audio systems
Focused on a Pre-Collision Assist / Automatic Emergency Braking feature developer to ensure core feature models are developed, integrated into a central ADAS ECU, meet systems engineering, and meet the expected acceptance criteria through proper test methods.
Compensation
This position is a range of salary grades 6-7 and ranges from $85,400 - $134,000.
Responsibilities
Lead overall feature model integration with other feature models according to the ADAS ECU software schedule.
Support model peer reviews of existing, modified and future feature model.
Support resolution of model integration compatibility issues with the larger feature model team or with the coding team.
Interface with the module teams that make up the overall distributed feature (ABS, PCM, IPC, AHU, etc.) to ensure system level function and requirements are met.
Lead/Support development of test methods to evaluate true positive, false positive and real-world performance criteria.
Ephla Bio is looking for a bioinformatician to turn biological and experimental data into insights that guide therapeutic development. Build reproducible analysis pipelines, interpret complex datasets, and apply statistical methods to target prioritization.
Locations (3)
Toronto, Ontario, Canada
San Francisco Bay Area, California, United States
New York, New York, United States
Responsibilities
Build and validate workflows from tumor/normal sequencing (WES/WGS, RNA-seq) through QC, somatic variant calling, VAF and clonality analysis (truncal vs. subclonal, adjusted for purity and copy number), HLA typing, expression quantification, and reporting.
Analyze HTS data and other large-scale screens. Integrate them with public datasets (e.g. immunopeptidomics) and turn patterns into testable hypotheses.
Assess assay quality, batch effects, and biological variability. Benchmark methods, validate findings against independent datasets or experimental results, and communicate uncertainty early.
Lead and own the entire technical stack, including Shopify store, internal AI tools, mobile app, infrastructure, and security, while managing a small team of developers and designers.
Compensation
Very competitive, set with the person. We would rather hear your expectation than anchor you with a number.
Responsibilities
Own and maintain the Shopify store, apps, and checkout integrations
Implement and manage A/B testing and site changes
Take over, harden, and build AI-assisted internal tools
Scope, develop, and launch iOS and Android mobile apps
Combine assay results, sequence annotations, and relevant biological evidence to rank candidates and explain the rationale for experimental follow-up.
Design experiments with lab scientists (scale, controls, data priorities), turn predictions into testable candidates, and feed results into the next round.