Senior Machine Learning Engineer (AI Tools) Job at SmartRecruiters

Senior Machine Learning Engineer, Shopping AI

As the engine behind Zillow Group's mission to build a seamless digital real est...

Location

United States

Salary:

163200.00 - 274300.00 USD / Year

Zillow

Expiration Date

Until further notice

Requirements

3-5 years of experience in developing applications in search, personalized ranking, or recommender systems
Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
Strong programming skills in a high-level language such as Python or Java
Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring

Job Responsibility

Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications
Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces
Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap
Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling
Act as a key technical voice, mentoring other engineers and helping to shape the long-term vision for artificial intelligence in the home shopping experience

What we offer

Equity awards

Fulltime

Senior Research Engineer Machine Learning, AI for Science

At Microsoft Research AI for Science we believe deep learning has the potential ...

Location

Germany , Berlin

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Completed MSc in computer science, machine learning, AI or a related area
Proficiency in collaborative software engineering in Python
Familiarity with Linux and the open-source ecosystem
In-depth understanding of open-source machine learning frameworks such as PyTorch and/or Jax
Experience in designing, developing and deploying ML systems
Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs
Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds

Job Responsibility

Develop and maintain tools, models and technologies for building, training, optimizing and scaling machine learning solutions
Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data
Build and optimize distributed data processing and model building pipelines
Prepare and maintain open-source releases and releases for internal and external beta testers
Work cross-functionally with machine learning researchers, engineers and researchers from the natural sciences
Maintain high standards in code quality and software design
Document and share best practices across the organization

Fulltime

Senior Machine Learning Engineer, Generative AI Products

Lead comprehensive applications/web development for highly complex projects; typ...

Location

United States , Boston

Salary:

Not provided

HBS

Expiration Date

Until further notice

Requirements

Minimum of seven years’ post-secondary education or relevant work experience
Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired
Minimum of five years’ software development experience with Python and SQL
Minimum of three years’ experience building pipelines to deploy NLP and deep learning models into production in a cloud environment
Minimum three years’ experience using PyTorch, Tensorflow, or MXNet, along with optimizing code for GPU clusters
Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools
Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications using tools such as NeMo
Experience with various embedding models and setting up and tuning vector databases to improve performance of semantic search and retrieval systems
Understand the underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs
Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka

Job Responsibility

Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents
Architect, build, maintain, and improve new and existing suite of GenAI applications and their underlying systems
Automate machine learning pipelines, monitor performance and costs, and optimize models by using techniques such as LoRA/QLoRA
Establish reusable frameworks to streamline model building, deployment and monitoring
Incorporate comprehensive monitoring, logging, tracing, and alerting mechanisms
Build guardrails, compliance rules and oversight workflows into the GenAI application platform, such as establishing approval chains for model updates and staged rollout for production releases
Develop templates, guides and sandbox environments for easy onboarding of new contributors and experimentation with new techniques
Ensure development of user-facing applications in the GenAI application platform is easy and safe by enforcing rigorous validation testing before publishing user-generated models and implement a clear peer review process of applications
Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value
Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps

What we offer

Generous paid time off including parental leave
Medical, dental, and vision health insurance coverage starting on day one
Retirement plans with university contributions
Wellbeing and mental health resources
Support for families and caregivers
Professional development opportunities including tuition assistance and reimbursement
Commuter benefits, discounts and campus perks

Fulltime

Senior Machine Learning Engineer, Data for Embodied AI

The goal of this role is to build, scale, and optimise next-generation world mod...

Location

United Kingdom , London

Salary:

Not provided

Wayve

Expiration Date

Until further notice

Requirements

Experience in ML engineering, data engineering, or applied ML roles focused on large-scale data systems
Proven experience building and maintaining large-scale data pipelines for machine learning, including data ingestion, transformation, and validation
Strong Python fundamentals and experience with modern ML and data frameworks (e.g. PyTorch, Ray, Dask, Spark, or equivalent)
Solid understanding of multimodal data (video, lidar, sensor telemetry) and its challenges in large-scale training
Experience defining and tracking data quality metrics, conducting dataset analysis, and driving data-informed improvements in model performance
Demonstrated ability to work collaboratively with ML researchers, platform engineers, and product teams in a fast-paced, experimental environment
Strong problem-solving skills, a data-driven mindset, and the ability to translate research needs into reliable data solutions

Job Responsibility

Design and implement large-scale data acquisition, processing, and curation pipelines, owning the full lifecycle of high-quality datasets used to train advanced robotics and foundation models
Continuously improve dataset quality and utility through sophisticated data analysis, debugging, and experimentation
developing metrics, tests, and monitoring mechanisms that directly drive model performance improvements
Develop and scale multimodal data pipelines for ingestion, preprocessing, filtering, annotation, and storage across video, LiDAR, and telemetry modalities
Run systematic experiments on data ablations and composition to assess their impact on model training dynamics, generalisation, and downstream performance
Collaborate with ML researchers and platform engineers to ensure datasets are fit for purpose and efficiently integrated into large-scale training workflows
Build internal tools and workflows for dataset auditing, visualization, and versioning to streamline iteration and reproducibility
Advance best practices for data governance, reliability, and scalability across the data lifecycle
ensuring data safety, privacy, and long-term maintainability

Senior Machine Learning Engineer, Data for Embodied AI

The goal of this role is to build, scale, and optimise next-generation world mod...

Location

United Kingdom , London

Salary:

Not provided

Wayve

Expiration Date

Until further notice

Requirements

Experience in ML engineering, data engineering, or applied ML roles focused on large-scale data systems
Proven experience building and maintaining large-scale data pipelines for machine learning, including data ingestion, transformation, and validation
Strong Python fundamentals and experience with modern ML and data frameworks (e.g. PyTorch, Ray, Dask, Spark, or equivalent)
Solid understanding of multimodal data (video, lidar, sensor telemetry) and its challenges in large-scale training
Experience defining and tracking data quality metrics, conducting dataset analysis, and driving data-informed improvements in model performance
Demonstrated ability to work collaboratively with ML researchers, platform engineers, and product teams in a fast-paced, experimental environment
Strong problem-solving skills, a data-driven mindset, and the ability to translate research needs into reliable data solutions

Job Responsibility

Design and implement large-scale data acquisition, processing, and curation pipelines, owning the full lifecycle of high-quality datasets used to train advanced robotics and foundation models
Continuously improve dataset quality and utility through sophisticated data analysis, debugging, and experimentation
developing metrics, tests, and monitoring mechanisms that directly drive model performance improvements
Develop and scale multimodal data pipelines for ingestion, preprocessing, filtering, annotation, and storage across video, LiDAR, and telemetry modalities
Run systematic experiments on data ablations and composition to assess their impact on model training dynamics, generalisation, and downstream performance
Collaborate with ML researchers and platform engineers to ensure datasets are fit for purpose and efficiently integrated into large-scale training workflows
Build internal tools and workflows for dataset auditing, visualization, and versioning to streamline iteration and reproducibility
Advance best practices for data governance, reliability, and scalability across the data lifecycle
ensuring data safety, privacy, and long-term maintainability

Senior Machine Learning Engineer, Reinforcement Learning

About the Role: We are looking for a Senior Machine Learning Engineer with stron...

Location

United States , Beverly Hills, CA

Salary:

150000.00 - 185000.00 USD / Year

Snail Games

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems
Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas
Strong Python skills and experience with modern ML frameworks such as PyTorch
Experience designing experiments, evaluating model behavior, and improving results through systematic iteration
T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning
Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments
Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it

Job Responsibility

Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches
Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior
Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility
Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity
Work closely with engineers and other partners to help integrate successful ML work into usable product systems
Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve

What we offer

True focus on work/life balance
Paid company holidays, vacation, and separate sick leave
Medical, dental, vision, and Life/LTD
401k with company match

Fulltime