machine learning engineer

RZR Global Inc.

<div>Who are we? 
 
RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC. 
<h4 class="jobSectionHeader">
Role Overview</h4>

We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
<h4 class="jobSectionHeader">
Key Responsibilities</h4>
<ul>
<li>Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
</li>
<li>Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
</li>
<li>Analyze the impact of integrating new data sources and features into our models.
</li>
<li>Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
</li>
<li>Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
</li>
<li>Document experiments, assumptions, and outcomes; maintain reproducibility
</li>
</ul><h4 class="jobSectionHeader">Required Skills / Experience</h4>
<ul>
<li>Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.
</li>
<li>At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.
</li>
<li>Experience with machine learning techniques such as regression, classification, and clustering.
</li>
<li>Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
</li>
<li>Strong grasp of probability, statistics, and data analysis principles.
</li>
<li>Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
</li>
</ul><h4 class="jobSectionHeader">Nice-to-Have</h4>
<ul>
<li>Familiarity with system programming languages including C++ and Rust is a plus.
</li>
<li>Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
</li>
<li>Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.</li></ul></div>

Machine Learning Engineer

Kodiak

<div><div>Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI) powered technology stack purpose-built for commercial trucking and the public sector. The company delivers freight daily for its customers across the southern United States using its autonomous technology. In 2024, Kodiak became the first known company to publicly announce delivering a driverless semi-truck to a customer. Kodiak is also leveraging its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense.</div><div>

Kodiak is seeking Machine Learning Engineers focussing on model deployment to help build the intelligence that powers the Kodiak Driver. Our ML teams work across perception, prediction, planning, and AI infrastructure to turn real-world driving data into models that enable safe and scalable autonomous trucking.

In this role, you will design and deploy machine learning systems that improve our vehicles' ability to understand the world, predict the behavior of other road users, and make safe driving decisions. You will collaborate closely with robotics, autonomy, and infrastructure teams to continuously improve the performance of our autonomy stack using large-scale data from our growing fleet.
This is a high-impact opportunity to work on cutting-edge AI systems operating in the real world, where every mile driven improves our models and brings autonomous trucking closer to global deployment. 
 
In this role, you will:</div>
<ul><li>Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.</li>
<li>Help identify and achieve parity between onboard and deployed offboard models using validation on HIL</li>
<li>Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.</li>
<li>Analyze real-world driving logs to identify edge cases and improve model robustness and safety.</li>
<li>Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.</li>
<li>Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak's fleet.</li>
</ul><div>What you'll bring:</div>
<ul><li>MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience. 
Strong experience deploying machine learning or deep learning systems in production environments.</li>
<li>Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.</li>
<li>Experience working with large-scale distributed training systems.</li>
<li>Solid understanding of optimization, and machine learning fundamentals.</li>
<li>Strong software engineering fundamentals including testing, debugging, and system design.</li>
<li>Ability to work collaboratively across teams to solve complex autonomy and robotics challenges.</li>
</ul>
What we offer:
<ul>
<li>Competitive compensation package including equity and annual bonuses</li>
<li>Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits)</li>
<li>MetLife Legal Services, Identity &amp; Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, &amp; Critical Illness Insurance</li>
<li>Flexible PTO, 10 paid holidays, and generous parental leave policies</li>
<li>Our office is centrally located in Mountain View, CA</li>
<li>Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging</li>
<li>Long Term Disability, Short Term Disability, Life Insurance</li>
<li>Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation)</li>
<li>Fidelity 401(k)</li>
<li>Commuter, FSA, Dependent Care FSA, HSA</li>
<li>Various incentive programs (referral bonuses, patent bonuses, etc.)</li>
</ul><div></div><div>
<div>At Kodiak, we strive to build a diverse community working towards our common company goals in a safe and collaborative environment where harassment of any kind is strictly prohibited. Kodiak is committed to equal opportunity employment regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or veteran status, or any other basis protected by applicable law.</div>
<div></div>
<div>In alignment with its business operations, Kodiak adheres to all relevant statutes, regulations, and administrative prerequisites. Accordingly, roles that carry more sensitive requirements may be limited to candidates that can satisfy additional scrutiny and eligibility for such positions may hinge on verification of a candidate's residence, U.S. person status, and/or citizenship status. Should the position require, and Kodiak determines that a candidate's residence, U.S. person status, and/or citizenship status necessitate an export license, bar the candidate from the position, or otherwise fall under national security-related restrictions, Kodiak will consider the candidate for alternative positions unaffected by such restrictions, under terms and conditions set forth at Kodiak's sole discretion, or, as an alternative, opt not to proceed with the candidate's application. If applicable, Kodiak may provide visa sponsorship for eligible candidates.</div>
<div></div>
<div>We use a third-party AI tool (Endorsed) to assist in the initial screening of applications. As part of the evaluation process, we provide Endorsed with job requirements and candidate-submitted applications. Final hiring decisions are made by our human recruitment team, and no automated system makes the ultimate decision regarding hiring. Certain features of the platform may qualify it as an Automated Employment Decision Tool (AEDT) under applicable regulations. We began using Endorsed on January 1, 2026. You can review the independent bias audit report covering our use of Endorsed [here](https://endorsed.com/local-law-144). By submitting your application, you acknowledge that your application may be processed by AI systems as part of the screening and selection process. If you have any questions or would like to request a separate review of your application, please contact careers@kodiak.ai with &quot;Separate Review Request&quot; in the email subject line.</div></div></div>

Machine Learning Engineer - Deployment

PRAVAH

<div><h2 class="jobSectionHeader">Staff Machine Learning Engineer, Computer Vision</h2><h3 class="jobSectionHeader"> 

About Pravah</h3>
Pravah is building foundational intelligence for the electric grid. We apply modern machine learning to complex physical infrastructure problems spanning grid operations, weather, and geospatial systems.
Our work sits at the intersection of computer vision, physical systems, and large-scale ML, with deployments across utilities in the United States and India. We leverage multimodal data - including satellite imagery, LiDAR, and street-level data - to build high-fidelity representations of grid assets and their surroundings.
We are backed by Khosla Ventures, Pear VC, and Conviction. 
 
To know more about who we are, what we are building, and why we are excited read this Notion! 
https://pravah.notion.site/<h3 class="jobSectionHeader">
The Role</h3>
We are hiring a Staff Machine Learning Engineer (Computer Vision) to lead the development of core perception and mapping systems for electric grid infrastructure.
This is a high-ownership, high-ambiguity role focused on building systems that operate on large-scale, heterogeneous visual data. You will define technical direction, make key architectural decisions, and ship models that are deployed in production.
Beyond core CV work, you will explore how state-of-the-art generative and vision architectures (e.g., ViTs, diffusion, flow matching) can be adapted to adjacent domains such as weather and spatiotemporal modeling.
There is also an opportunity to contribute to frontier work suitable for publication, particularly in areas where existing methods do not translate cleanly to real-world physical systems.<h3 class="jobSectionHeader">
What You&rsquo;ll Work On</h3>
Grid Mapping &amp; Infrastructure Understanding<ul><li>
Build and deploy models for object detection, segmentation, and instance-level understanding of grid assets and surroundings</li><li>
Work across satellite, aerial, street view, and LiDAR data to create unified representations of physical infrastructure</li><li>
Develop systems for depth estimation and spatial reasoning in complex real-world environments</li></ul> 
Multimodal &amp; Foundation Models<ul><li>
Adapt and fine-tune vision transformers and related architectures for domain-specific tasks</li><li>
Build multimodal systems that combine visual, spatial, and structured data 
Design representations that generalize across geographies, data sources, and operating conditions</li></ul> 
Applied Research &amp; New Directions<ul><li>
Bring state-of-the-art CV methods into production, bridging research and real-world deployment</li><li>
Explore the use of modern generative and vision architectures in weather and geospatial modeling applications</li><li>
Identify, prototype, and validate new approaches for modeling physical systems from visual data</li></ul><h3 class="jobSectionHeader"> 
Who You Are</h3><ul><li>
6+ years of experience building and deploying machine learning systems, with a focus on computer vision</li><li>
Strong expertise in modern deep learning approaches, including:<ul><li>
Object detection and segmentation</li><li>
Vision transformers and/or generative modeling approaches</li><li>
Multimodal learning</li></ul></li><li>
Proven track record of taking systems from research to production at scale</li><li>
Strong engineering fundamentals and proficiency in Python and ML frameworks (e.g., PyTorch)</li><li>
Experience working with large-scale, real-world datasets (e.g., geospatial, satellite, LiDAR) is a strong plus</li><li>
Comfortable operating in ambiguous environments, reasoning from first principles, and driving technical direction with high ownership</li><li>
Demonstrated ability to produce high-quality technical work, whether through systems, research, or publications</li></ul><h3 class="jobSectionHeader">
What You&rsquo;ll Gain</h3><ul><li>
Ownership of core perception and mapping systems deployed in real-world grid operations</li><li>
Opportunity to work on hard, open-ended problems at the intersection of AI and physical infrastructure</li><li>
Ability to shape technical direction and contribute to frontier ML work</li><li>
Close collaboration with a deeply technical founding team</li></ul><h3 class="jobSectionHeader">
Why This Role</h3>
This role sits at the frontier of applying modern computer vision to large-scale physical systems. Many of the problems we work on do not have established benchmarks or standard solutions. You will operate in settings where data is heterogeneous, ground truth is incomplete, and progress requires both technical depth and first-principles thinking.
Compensation Range: $150K - $200K</div>

Staff Machine Learning Engineer (Computer Vision)

Uber

<div>About the Role
 
 
Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
 
 
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
 
 
What You Will Do
<ul><li>Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
</li><li>Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
</li><li>Collaborate with the team leads to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
</li><li>Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
</li></ul>Basic Qualifications
<ul><li>Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
</li><li>4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions
</li><li>Proficiency in programming languages such as Python, Scala, Java, or Go
</li><li>Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
</li><li>Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
</li><li>Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization)
</li></ul>Preferred Qualifications
<ul><li>Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
</li><li>Experience leading complex technical projects and influencing the scope and output of others
</li><li>Track record of translating ambiguous business problems into technical solutions and driving multi-functional projects
</li><li>Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
</li>Experience in reinforcement learning and causal machine learning 
<li>
</li></ul> 
 
For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Sr Machine Learning Engineer, Pricing

Amaris Consulting

Job description
 
The Opportunity
 
Amaris Consulting is looking for a Software / Machine Learning Engineer to join a world-class engineering team working on cutting-edge autonomous and operator-assist systems. You will contribute to building production-grade autonomy software, from perception and computer vision to real-time decision-making; on both robotic and manned platforms. A high-impact role at the intersection of AI, robotics, and safety-critical systems.
 
Your Key Responsibilities
 
Design, implement and test algorithms for autonomy and advanced operator-assist systems
 Develop and maintain production-quality C++ and Python code for autonomy features
 Collect, process and analyze data from robotic and manned platforms to improve ML models and system performance
 Participate in the full software development lifecycle using Agile practices
 Contribute to architecture decisions, design reviews, code reviews and technical documentation, including design specs, test plans and safety procedures
 
Skills And Attributes For Success
 
Solid AI / ML / Deep Learning background applied to autonomy or operator-assist systems
 Strong experience in computer vision — image processing, object detection, tracking, scene understanding
 Hands-on experience with TensorFlow and/or PyTorch, and OpenCV for perception and sensor data processing
 Proficiency in C++ and Python for production-grade software development
 Extensive experience with Agile SDLC using Azure DevOps or Jira
 Comfortable with cloud compute and storage; AWS EC2, S3, Batch, for training, testing and deployment workflows
 Experience developing, integrating and testing complex autonomy software under safety and timing constraints
 Degree in Computer Science, Engineering, Robotics or a related field
 
Ideally, You'll Also
 
Have familiarity with ROS or AIS for robotics software development
 Have experience with NVIDIA hardware for accelerated ML workloads
 Be comfortable working across multiple subsystems and debugging complex cross-system issues
 Have exposure to safety-critical software development standards and practices
 
What We Look For
 
A curious and rigorous engineer who thrives at the intersection of AI research and real-world deployment. You write clean, reliable code, take ownership of your work end to end, and communicate clearly across robotics, systems and product teams. You are energized by hard problems and motivated by seeing your algorithms perform in the real world, not just on paper.
 
Why choose us
 
An international community bringing together more than 110 different nationalities
 An environment where trust is central: 70% of our leaders started their careers at the entry level
 A strong training system with our internal Academy and more than 250 modules available
 A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.)
 
Amaris Consulting promotes equal opportunities. We are committed to bringing together people from diverse backgrounds and creating an inclusive work environment. In this regard, we welcome applications from all qualified individuals, regardless of sex, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics.
 
Who are we?
 Amaris Consulting is an independent technology consulting firm providing guidance and solutions to businesses. With more than 1000 clients across the globe, we have been rolling out solutions in major projects for over a decade – this is made possible by an international team of 7,600 people spread across 5 continents and more than 60 countries. Our solutions focus on four different Business Lines: Information System & Digital, Telecom, Life Sciences and Engineering. We’re focused on building and nurturing a top talent community where all our team members can achieve their full potential. Amaris is your steppingstone to cross rivers of change, meet challenges and achieve all your projects with success.
 
At Amaris, we strive to provide our candidates with the best possible recruitment experience. We like to get to know our candidates, challenge them, and be able to give them proper feedback as quickly as possible. Here's what our recruitment process looks like:
 
Brief Call: Our process typically begins with a brief virtual/phone conversation to get to know you! The objective? Learn about you, understand your motivations, and make sure we have the right job for you!
 
Interviews (the average number of interviews is 3 - the number may vary depending on the level of seniority required for the position). During the interviews, you will meet people from our team: your line manager of course, but also other people related to your future role. We will talk in depth about you, your experience, and skills, but also about the position and what will be expected of you. Of course, you will also get to know Amaris: our culture, our roots, our teams, and your career opportunities!
 
Case study: Depending on the position, we may ask you to take a test. This could be a role play, a technical assessment, a problem-solving scenario, etc.
 
As you know, every person is different and so is every role in a company. That is why we have to adapt accordingly, and the process may differ slightly at times. However, please know that we always put ourselves in the candidate's shoes to ensure they have the best possible experience.
 We look forward to meeting you!

Software / Machine Learning Engineer - Autonomous Systems

Catalyst Labs

<div>
 
 About The Job ML Engineer
 
 
 
 
 Our Client
 
 
 
 Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.
 
 
 By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
 
 
 
 About Us
 
 
 
 Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that&rsquo;s deeply embedded in our clients&rsquo; recruitment operations.
 
 
 We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.
 
 
 
 Location
 
 : New York, NY
 
 
 
 Work type
 
 : Full Time,
 
 
 
 Compensation
 
 : above market base + bonus + equity
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 </li>
 <li>
 Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 </li>
 <li>
 Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 </li>
 <li>
 Build agents capable of operating natively on real-world audio inputs.
 </li>
 <li>
 Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 </li>
 <li>
 Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 </li>
 <li>
 Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 </li>
 <li>
 Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
 </li>
 <li>
 1-6 years of professional experience in ML engineering.
 </li>
 <li>
 Strong programming skills in Python (TypeScript experience is a plus).
 </li>
 <li>
 Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Familiarity with cloud environments and infrastructure (preferably AWS).
 </li>
 <li>
 Strong understanding of data pipeline design, real-time inference, and model monitoring.
 </li>
 <li>
 Excellent communication skills with the ability to engage directly with customers and stakeholders.
 
 
 </li>
 </ul>
 
 Core Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying ML models into production environments.
 </li>
 <li>
 Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 </li>
 <li>
 Experience with audio-focused ML projects or similar domains involving unstructured data.
 </li>
 <li>
 Proficiency in building scalable data pipelines for model training and evaluation.
 </li>
 <li>
 Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 </li>
 <li>
 Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
 </li>
 </ul>
</div>

ML Engineer

Apple

Do you have a passion for invention and self-challenge? Do you thrive on pushing the limits of what&rsquo;s considered feasible? As part of a world class modem team, you&rsquo;ll craft sophisticated leading-edge embedded firmware that deliver more performance in our products than ever before. You&rsquo;ll work across disciplines to transform improved hardware elements into a single, integrated design. 
 
Join us, and you&rsquo;ll help us innovate new wireless systems technologies that continually outperform the previous iterations. By collaborating with other product development groups across Apple, you&rsquo;ll push the industry boundaries of what wireless systems can do and improve the product experience for our customers across the world. Do you want to have an impact on every single Apple product? As a Cellular Data &amp; Automation Engineer, you will be at the center of the embedded 5G/4G/multimode cellular firmware effort within a silicon design group responsible for designing and productizing state-of-the-art cellular SoCs. 
 
Description 
 
As a Data &amp; Automation Engineer, you will be responsible for developing new features to enhance test automation system for improving test efficiency and stability. Furthermore, you will be participating in developing state-of-the-art data processing pipeline and leveraging data science algorithms &amp; machine learning models to parse massive data and logs in timely manner to automatically solve the issues or provide recommendations for the next step. In addition, you will be closely partnering with FW engineering teams in integrating and deploying models and data processing pipeline as part of entire automation system to deliver analysis results to benefit FW engineers in debugging issues. You will work with amazing team, brainstorm new ideas, and develop models and algorithms to solve complicated problems that have a substantial impact.&quot;,&quot;responsibilities&quot;:&quot;Develop new features to enhance the automation system based on the business&rsquo;s needs 
 
Develop and maintain real-time data processing pipelines to ensure processing accuracy and efficiency 
 
Collaborate closely with AI/ML engineers to integrate new AI pipelines and ML models into the production system and ensure achieving expected results and efficiency 
 
Integrate various internal tools and external tools into the existing automation system and/or data processing pipelines to enable new applications 
 
Provide technical support for users and help troubleshoot issues to unblock projects 
 
Preferred Qualifications 
 
Master&rsquo;s degree in data science or computer science or machine learning is preferred. 
 
Proficient in scripting or programming languages such as Python, Java, C/C++ with 5+ years of proven programming skills. 
 
Advanced SQL skills with the ability to write complex joins and nested queries. 
 
Proficiency in data visualization tools (such as Tableau, D3) and strong understanding of data manipulation and querying using SQL and Python together. 
 
Experience with dashboards and interactive reports. Ability to work with large datasets and conduct data cleaning and transformation. 
 
Experience with automation tools and frameworks, e.g. Jenkins, Gitlab CI/CD. 
 
Ability to leverage data science algorithms and machine-learning models to solve various kinds of issues. 
 
Experience in utilizing analytics and statistical methods to transform data into useful insights and actionable results. 
 
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes. 
 
Strong critical thinking and communication skills with the ability and desire to learn and evaluate new technologies. 
 
Minimum Qualifications 
 
BS and a minimum of 3 years relevant industry experience. 
 
Proficient developer with 3+ years proven programming skills using Python, Pandas, Matplotlib and other key related tools. 
 
Solid knowledge and experience with relational database (e.g Postgres) and non-relational database (e.g.Mango DB). Ability to write complex queries with SQL is required. 
 
Experience with dashboards and interactive reports. Proficiency in data visualization tools (such as Tableau) and a strong understanding of data manipulation and querying using SQL and Python together. 
 
Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Cellular Data & Automation Engineer

Explore 148+ Machine learning engineer in San Francisco this April. Find roles across top companies and apply now to boost your career.