Senior Lead Machine Learning Engineer Job at Reqiva (Brisbane)

Senior Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...

Location

United States , New York; San Francisco; San Jose; Cambridge; McLean

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor’s Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems
Inform ML infrastructure decisions using understanding of ML modeling techniques
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate as part of a cross-functional Agile team to create and enhance software
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Leverage continuous integration and continuous deployment best practices
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
Use programming languages like Python, Scala, or Java

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Fulltime

Senior Lead Machine Learning Engineer

At Capital One, we are creating responsible and reliable AI systems, changing ba...

Location

United States , New York; San Francisco; San Jose; Cambridge; McLean

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor’s Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with a cross-functional team of engineers, research scientists, technical program managers, and product managers
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more
Construct optimized data pipelines to feed ML models
Design, develop, test, deploy, and support AI software components including large language model inference, similarity search, model evaluation, experimentation, governance, and observability, etc
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI

What we offer

comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Fulltime

Senior / Lead Machine Learning Engineer, Serving

Inworld is a product-oriented research lab of top AI researchers and engineers, ...

Location

Germany

Salary:

Not provided

Inworld AI

Expiration Date

Until further notice

Requirements

Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM
Model Acceleration. Hands-on experience with quantization, distillation, caching strategies, continuous batching, paged attention, and speculative decoding
High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs
Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections
Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups
Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production
Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems
Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams

Senior / Lead Machine Learning Engineer, Serving

Location

Serbia

Salary:

Not provided

Inworld AI

Expiration Date

Until further notice

Requirements

Inference Optimization
Model Acceleration
High-Performance Systems
Distributed Systems & Scaling
Public work
Full-cycle ownership
Background
Professional fluency in English

Senior Machine Learning Engineer (Team Lead)

As our Artificial Intelligence (AI) and Machine Learning (ML) Team Leader, you w...

Location

Australia , South Bank

Salary:

Not provided

Flight Centre Brand

Expiration Date

Until further notice

Requirements

7+ years delivering production grade ML or AI systems with proven commercial impact
3+ years Leading and Mentoring engineers
Experience building AI agents, RAG systems or LLM powered applications in production
Demonstrated experience leading technical teams and managing complex AI programmes
Strong hands on experience across ML infrastructure, distributed systems and scalable AI architecture
Experience building and governing AI agent platforms including endpoints, gateways and tool orchestration
Familiarity with MCP servers and emerging agent communication standards and protocols
Experience defining evaluation frameworks, safety mechanisms and governance for LLM and agent based systems
Deep knowledge of Python, modern AI/ML frameworks and scalable AI platforms including Databricks
Strong expertise in Kubernetes and cloud native production environments

Job Responsibility

Lead the development and productionisation of ML models, LLM powered systems and agent based applications
Define and build end to end MLOps including CI CD, model registry, monitoring, drift detection and retraining for predictive ML systems
Establish LLMOps standards including context engineering, automated evaluation pipelines, red teaming, safeguards and policy guardrails
Architect and build AI agent workflows, endpoints, gateways and orchestration layers enabling secure tool access, structured reasoning and multi agent collaboration
Design and govern MCP servers and modern agent communication protocols to ensure interoperability, security and scalability
Implement strong observability across ML and GenAI systems including reliability, latency, evaluation metrics, usage tracking and cost control
Drive scalable ML infrastructure, feature stores and data platforms on Databricks
Oversee Kubernetes based deployments and cloud native AI infrastructure
Partner with senior stakeholders to prioritise and deliver multiple high impact AI initiatives
Coach and grow a high performing AI engineering team

What we offer

Individualised, ongoing Learning & Development via communities of practice
Innovation Days
Dedicated Engineering Days
Access to 'LinkedIn Learning' for ongoing skills development
Women in PM&E group
Exclusive Staff Discounts
Travel Discounts
Career opportunities in a network of brands and businesses across the globe
Corporate Health Discounts
Mental Health Support and Employee Assistance Program for staff and family

Fulltime

Senior Machine Learning Engineer, AI Platform

The AI Platform team is responsible for building the foundational infrastructure...

Location

United States; Canada

Salary:

139000.00 - 218000.00 USD / Year

Mozilla

Expiration Date

Until further notice

Requirements

Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
Hands-on experience working with GPU-based workloads and accelerated computing in production settings
Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
Ability to independently scope and drive technical initiatives while balancing product and operational priorities
Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams

Job Responsibility

Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews

What we offer

Generous performance-based bonus plans
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Senior Machine Learning Engineer – AV Labs

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We'...

Location

United States , Sunnyvale

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

4+ years of working experience in the ML/Robotics industry
Bachelor's degree in Computer Science, Computer Engineering, or related fields
Proficient in Python and Linux environments
Familiar with modern AI/ML frameworks (e.g., PyTorch).

Job Responsibility

Algorithm Development: Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake
Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies
Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability
Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling
Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.

What we offer

Bonus program
Equity award & other types of comp
401(k) plan
Various benefits

Fulltime

Senior Machine Learning Engineer, Search Assistant

Roku is changing how the world watches TV. Roku is the #1 TV streaming platform ...

Location

United States , San Jose

Salary:

361300.00 - 510000.00 USD / Year

Roku

Expiration Date

Until further notice

Requirements

8+ years of industry experience (or PhD with 5+ years) applying ML at scale in search, recommendation, ads, personalization, or related domains
Strong expertise in ranking systems, recommendation systems, retrieval, personalization, and multi-objective optimization
Experience building large-scale ML systems leveraging deep learning, sequence models, LLMs, reinforcement learning, or bandit frameworks
Strong product intuition and experience optimizing user engagement, retention, and monetization simultaneously
Proficiency in Python, Java, or Scala
Experience with distributed systems and ML infrastructure such as Spark, Airflow, streaming systems, feature stores, and cloud platforms
Strong technical leadership, system design, communication, and problem-solving skills
MS or PhD in Computer Science, Statistics, or a related field

Job Responsibility

Lead the technical vision and roadmap for ranking, personalization, and recommendation systems powering Roku’s entertainment assistant
Develop and deploy state-of-the-art ML models using deep learning, transformers, LLMs, bandits, reinforcement learning, and causal inference techniques
Build multi-objective optimization systems balancing engagement, retention, relevance, and monetization goals
Drive innovation in conversational discovery, contextual recommendations, and personalized content experiences across the platform
Design, run, and analyze online A/B experiments tied to key product and business KPIs
Architect scalable ML systems, feature platforms, and data pipelines supporting rapid experimentation and long-term growth
Mentor engineers and provide technical leadership across cross-functional initiatives involving engineering, product, UX, and analytics teams

What we offer

Health insurance
Equity awards
Life insurance
Disability benefits
Parental leave
Wellness benefits
Paid time off
Global access to mental health and financial wellness support and resources
Healthcare (medical, dental, and vision)
Life, accident, disability, commuter, and retirement options (401(k)/pension)

Fulltime

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Senior Lead Machine Learning Engineer

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