machine learning engineer

Hadrian

<div>
 
 Hadrian - Manufacturing the Future
 
 
 
 Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts.
 
 
 We&rsquo;re accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts.
 
 
 Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond.
 
 
 
 The Role
 
 
 
 Hadrian is building advanced software systems to automate Design for Manufacturing (DFM) analysis and accelerate precision manufacturing. Our homebuilt DFM platform analyzes design prints and CAD models to make logical, data-driven determinations about whether and how Hadrian can manufacture a part.
 
 
 We work closely with some of the best operators in the world to identify high-impact opportunities where software, computer vision, and machine learning can meaningfully augment or automate complex engineering judgment. As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Research, develop and deploy cutting-edge deep learning models, including OCR, vision-language, and detection models for document understanding and layout analysis
 </li>
 <li>
 Contribute to the ongoing development and refinement of current models in close collaboration within the engineering team and end users
 </li>
 <li>
 Work in every facet of the Machine Learning lifecycle - including the creation and optimization of production data pipelines, and software systems for training, inference, labeling, and evaluation
 </li>
 <li>
 Judiciously combine open-source solutions and novel research to create world-class vision systems for manufacturing applications
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Bachelors in Computer Science, Electrical Engineering, Mechanical Engineering (or similar discipline), or an equivalent amount of deep learning experience
 </li>
 <li>
 5+ years of experience in Computer Vision and/or Machine Learning, including ownership of projects throughout the entire ML Lifecycle
 </li>
 <li>
 Proficiency in Python, OpenCV, SQL, and one or more deep learning frameworks (PyTorch, Tensorflow, etc.)
 
 
 </li>
 </ul>
 
 What Sets You Apart
 
 
 
 <ul>
 <li>
 A Master&rsquo;s Degree in Computer Science with focus in Artificial Intelligence or Machine Learning
 </li>
 <li>
 Demonstrated experience with detection/segmentation models and achieving high performance results - including exploratory analysis, model selection, and hyperparameter tuning
 </li>
 <li>
 Previously worked in aerospace, defense, or manufacturing, and have experience working 3D/CAD/CAM data for manufacturing applications
 </li>
 <li>
 Strong software engineering skills and prior web development experience using Javascript/TypeScript or Python, and familiarity with FastAPI or Express frameworks
 </li>
 <li>
 Prior experience with distributed training using cloud infrastructure
 </li>
 <li>
 Prior experience with visual document understanding and layout analysis
 </li>
 <li>
 Published research or achieved SOA results on an ML application
 </li>
 <li>
 Prior experience with multi-modal deep learning models
 </li>
 <li>
 You have a passion for manufacturing and believe that the industry needs better software
 </li>
 <li>
 Prior experience working in a startup environment
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 For this role, the target salary range is $160,000 - $250,000 (actual range may vary based on experience).
 
 
 This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will be based on several factors, including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.
 
 
 
 Benefits For Full-time Employees
 
 
 
 <ul>
 <li>
 Medical, dental, vision, and life insurance plans for employees
 </li>
 <li>
 401k
 </li>
 <li>
 Relocation support may be provided for certain situations, based on business need.
 </li>
 <li>
 Flexible vacation policy
 
 
 </li>
 </ul>
 
 ITAR Requirements
 
 
 
 To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
 
 
 
 Hadrian Is An Equal Opportunity Employer
 
 
 
 It is the Company&rsquo;s policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions.
</div>

Machine Learning Engineer

MultiBank Group

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle &mdash; from model design through deployment, optimization, and ongoing performance in production &mdash; and contributes to the technical direction of the AI platform.
Key Responsibilities<ul><li>
Architect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day one</li><li>
Build and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scale</li><li>
Own technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainability</li><li>
Design and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applications</li><li>
Implement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelines</li><li>
Continuously optimize model performance, inference latency, cost efficiency, and reliability across live systems</li><li>
Collaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutions</li><li>
Mentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the team</li><li>
Contribute to strategic decisions around data architecture, AI infrastructure, and cloud platform direction</li><li>
Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimization</li></ul>
Requirements<ul><li>
7 to 15 or more years of experience in software engineering, data science, or ML engineering</li><li>
Strong background in product companies, scale-ups, or enterprise AI platforms</li><li>
Proven track record of building production-grade AI systems, not solely notebooks or proof-of-concept work</li><li>
Comfortable owning systems end-to-end from data through model through deployment through monitoring</li><li>
Product-first engineering approach, not research-only profiles</li><li>
Advanced Python engineering skills with strong systems thinking and a focus on production quality</li><li>
Comfortable with fast iteration cycles and deploying models into live environments</li><li>
Ability to work directly and confidently with stakeholders and product owners</li><li>
Fintech or financial services experience is an advantage</li></ul>
Technical Skills
Machine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)
LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelines
MLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacks
Cloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCP
Data Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architectures
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior Machine Learning Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Tesla

<div>What to Expect<div>
As a Machine Learning Engineer at Tesla AI working on Digital Optimus, you will build training, inference, data, and evaluation systems for frontier computer-use agents. These agents combine high-level reasoning models with real-time vision to ingest computer screen video, understand UIs, execute actions, and complete complex digital workflows autonomously.
We are looking for ML generalists or domain specialists with strong applied ML fundamentals who excel at turning research ideas into reliable production systems. 
</div> 
What You'll Do<div>
<ul><li>Build training pipelines that turn real agent interactions (screen data, actions, outcomes) into model improvements</li><li>
Design model architecture and training recipes to improve performance in a scientific way.</li><li>
Design evaluation frameworks and benchmarks to measure agent performance and identify failure modes</li><li>
Create data systems that extract high-quality signals from agent runs for continuous iteration</li><li>
Develop inference and model routing logic to combine reasoning and vision models efficiently in real time</li><li>
Ship end-to-end improvements that increase agent reliability and autonomy on long-horizon tasks</li></ul>
</div> 
What You'll Bring<div>
<ul><li>Strong applied ML fundamentals with a passion for turning research into robust, production-grade systems</li>
</ul><ul><li>Experience designing model architectures and/or building training workflows, evaluation tools, data pipelines, or inference optimizations</li>
</ul><ul><li>Solid software engineering skills and a high sense of ownership</li>
</ul><ul><li>Background in agentic systems and/or multimodal (vision + language) models</li>
</ul><ul><li>Excitement about making multimodal models reliable and effective in real-world agentic environments</li>
</ul><ul><li>Experience with post-training or RL methods (PPO, GRPO, RLHF) is a strong plus</li>
</ul></div> 
Compensation and Benefits<div>
Benefits</div><div>
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
<ul><li>Medical plans &gt; plan options with $0 payroll deduction</li>
<li>Family-building, fertility, adoption and surrogacy benefits</li>
<li>Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution</li>
<li>Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA</li>
<li>Healthcare and Dependent Care Flexible Spending Accounts (FSA)</li>
<li>401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits</li>
<li>Company paid Basic Life, AD&amp;D</li><li>
Short-term and long-term disability insurance (90 day waiting period)</li>
<li>Employee Assistance Program</li>
<li>Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays</li>
<li>Back-up childcare and parenting support resources</li>
<li>Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft &amp; legal services, and pet insurance</li>
<li>Weight Loss and Tobacco Cessation Programs</li>
<li>Tesla Babies program</li>
<li>Commuter benefits</li>
<li>Employee discounts and perks program</li>
</ul></div><div>Expected Compensation</div><div>
$124,000 - $420,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.</div> 
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. 
 
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.</div>

Machine Learning Engineer, Digital Optimus

Dyson

<div>
 
 About Us
 
 
 
 At Dyson, we&rsquo;re driven by a relentless pursuit of innovation&mdash;pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson&rsquo;s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.
 
 
 You&rsquo;ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.
 
 
 
 About The Role
 
 
 
 We are looking for a specialized Lead Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.
 </li>
 <li>
 Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.
 </li>
 <li>
 Quality Assurance &amp; Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.
 </li>
 <li>
 Tooling &amp; Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.
 </li>
 <li>
 Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.
 </li>
 <li>
 Set up and maintain robust data preparation infrastructure&mdash;optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.
 </li>
 <li>
 Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You&rsquo;ll help transform raw data into actionable insight, supporting both research and deployment.
 </li>
 <li>
 Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.
 
 
 
 </li>
 </ul>
 
 About you
 
 
 
 <ul>
 <li>
 At least 8+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.
 </li>
 <li>
 Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).
 </li>
 <li>
 Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).
 </li>
 <li>
 Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).
 </li>
 <li>
 Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.
 </li>
 <li>
 Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.
 </li>
 <li>
 Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.
 </li>
 <li>
 Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).
 </li>
 <li>
 Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).
 </li>
 <li>
 Strong background in feature engineering, data analysis, and data visualization&mdash;comfortable using tools like Jupyter, Tableau, or Power BI.
 </li>
 <li>
 Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.
 </li>
 <li>
 Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.
 </li>
 <li>
 Bachelor&rsquo;s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.
 
 
 
 </li>
 </ul>
 Dyson is an equal opportunity employer. We know that great minds don&rsquo;t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
</div>

Lead Data Intelligence Machine Learning Engineer

TikTok

<div></div><div><div>San Jose
<div></div>Regular
<div></div>R&amp;D
<div></div>Job ID: A146630A
</div><div>Responsibilities</div>
<div>About the team Pangle is the ad network of TikTok for Business, helping mobile developers accelerate growth, deliver engaging ad experiences, and maximize revenue by accessing TikTok's global advertising demand. Operating in more than 36 countries and regions, Pangle has built a strong reputation for driving measurable results for app partners worldwide. As Pangle expands into the U.S. market, we're building our advertising platform from the ground up &mdash; tackling exciting new challenges in large-scale systems, optimization, and machine learning. Join us to shape the future of mobile monetization and grow your career in a fast-moving, global team. Responsibilities - Develop and optimize bidding algorithms and strategies across Pangle's ad delivery systems, including targeting, retrieval, ranking, and bidding models, with a focus on improving monetization efficiency and overall ad ROI. - Improve the performance and efficiency of large-scale, online-learning&ndash;based deep models for real-time advertising applications. - Apply advanced modeling techniques and strategic thinking to enhance attribution accuracy, delivery quality, and long-term ecosystem sustainability. Identify and drive innovative commercialization technologies and product solutions. - Design, build, and iterate on core ad prediction models such as CTR (Click-Through Rate) and CVR (Conversion Rate) models.</div>
<div>Qualifications</div>
<div>Minimum Qualification(s): - Bachelor's degree in computer science or related technical disciplines. - 1+ years of hands-on experience with building and training complex and scalable machine learning systems. - Strong Computer Science fundamentals (algorithms, data structures, software design) and problem-solving skills. - Strong coding skills and a solid understanding of machine learning algorithms, particularly deep learning and ranking models. - Experience leading or driving machine learning projects. Preferred Qualification(s): - Strong theoretical background in machine learning and deep learning, with proficiency in at least one major framework (e.g., TensorFlow, PyTorch). - Demonstrated experience optimizing large-scale advertising systems, including bidding algorithms and delivery strategies. Familiarity with OCPC, OCPM, and AEO bidding models, and understanding of ad delivery mechanisms. - Excellent teamwork and communication skills, with a strong sense of ownership and the ability to move projects forward independently. - Strong business and data intuition, passion for tackling complex problems, and proven ability in abstraction, project execution, and innovation.</div>
<div>Job Information</div>
<div><div>【For Pay Transparency】Compensation Description (Annually)<div> 
<div>The base salary range for this position in the selected city is $136800 - $259200 annually. 
Compensation may vary outside of this range depending on a number of factors, including a candidate&rsquo;s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. 
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure). 
The Company reserves the right to modify or change these benefits programs at any time, with or without notice. 
For Los Angeles County (unincorporated) Candidates: 
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; 
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and 
3. Exercising sound judgment. 
</div></div></div><div>About USDS<div> 
<div>TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale. 
On-site presence across teams allows the company to operate with greater speed, alignment, and agility &mdash; especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week. 
</div></div></div><div>Why Join Us<div> 
<div>Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect &ndash; and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day. 
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an &quot;Always Day 1&quot; mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us. 
Diversity &amp; Inclusion 
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. 
</div></div></div><div>USDS Reasonable Accommodation<div> 
<div>USDS is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/USDS-RA</div></div></div></div></div>

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