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senior machine learning engineer ai platform

Smartly.io Solutions

<div><div>We are looking for a Senior Machine Learning Engineer to join the AI Platform Team at Smartly! Our team works on helping marketers make the most of their ad creatives (images, video, text) and campaigns (product and performance data). We build and experiment with AI-based solutions across the media and creative workflows.You will have the opportunity to take ownership of and work on high impact projects.

Join us in building high impact ML-based solutions to help our customers to build better and more effective advertising experiences for their consumers. If you&rsquo;re a growth minded individual who has a passion for ML and the marketing space, this team is for you!
<h2 class="jobSectionHeader">
As a Senior Machine Learning Engineer, you&rsquo;ll:</h2>
<ul><li>Build ML-based software systems that enable our users to craft great advertising experiences and campaigns</li>
<li>Work with a large span of datasets from image to video to audio to text to structured performance data.</li>
<li>Contribute to and strengthen Smartly&rsquo;s MLOps + data platform. You&rsquo;ll work alongside our stellar senior machine learning engineers, data scientists, and software engineers to enable us to productionize AI/ML applications more robustly and efficiently.</li>
<li>Be a core contributor of our team and our ways of working to build high impact products. You&rsquo;ll actively be involved in work planning, retrospectives, and overall team improvement.</li>
<li>Impact the daily life of the staff of the hundreds of advertisers using Smartly</li>
<li>Work with our stakeholders - be them product, engineering, infrastructure - to ensure we meet customers where they are. As with most ML-related roles, being able to translate business/product needs to viable solutions is a must.</li>
<li>Apply and enhance your soft skills through working closely with your colleagues and our customers. Doing knowledge shares, running productive meetings, and pair programming/debugging are just some ways we grow our soft skills.</li>
<li>Keep up to date with the latest ML innovations, especially in areas such as generative AI, computer vision, natural language processing and explainability.</li>
</ul><h2 class="jobSectionHeader">What we are looking for:</h2>
<ul><li>5+ years of experience developing and deploying production-quality software</li>
<li>2+ years of experience delivering software services powered by machine learning</li>
<li>2+ years of experience working with cloud infrastructure such as AWS or GCP</li>
<li>Fluent in Python; experience with C++ or Java is a plus</li>
<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>
<li>Knowledge of MLOps concepts and tools (e.g., MLflow, Kubeflow)</li>
<li>Experience in feature engineering, model evaluation, diagnostics, and monitoring</li>
<li>Strong foundation in linear algebra, statistics, and calculus</li>
<li>Experience building scalable data pipelines for ML-based data processing</li>
<li>Experience developing and maintaining services under SLA</li>
<li>Analytical mindset with a problem-solving approach</li>
<li>Passion for solving customer challenges quickly while making thoughtful architectural decisions</li>
<li>Adaptability and resilience when facing new or ambiguous challenges</li>
<li>Strong written and verbal communication skills in English</li>
<li>M.Sc. in a relevant field is preferred</li>
<li>Ability and willingness to work in a hybrid capacity from our office 3 days a week</li>
</ul><h2 class="jobSectionHeader">What We Offer You</h2>

At Smartly, we offer a place where you can advance your career. Here, you'll find:

An Inclusive Global Culture: Join a team of over 750 Smartlies, representing more than 60 nationalities across 24 locations in 13 countries. We cultivate a culture built on trust, transparency, and open feedback, where diverse perspectives are valued and encouraged.

Global Impact: Contribute to a company making a global impact, directly influencing our customers' success and business growth.

Focus on Wellbeing: We prioritize your health with healthcare packages, mental health services, and a commitment to work-life balance through paid holidays and family leave.

Comprehensive Rewards: Benefit from equity options, performance-based rewards, competitive compensation, and career development opportunities.

Flexible Hybrid Workplace: Experience a hybrid work model, balancing office collaboration with remote work, and the option to work abroad for up to 30 days annually. 


Apply Now and Build Your Future with Smartly!

Curious what it&rsquo;s like to work at Smartly?</div></div>

Senior Machine Learning Engineer, AI Platform

Code Compass 🧭

<div>
 
 🤖 Machine Learning Engineer &ndash; Computer Vision &amp; Generative AI &ndash; 100%
 
 
 
 
 
 📍 Berlin, Germany | 💰 &euro;50,000 - &euro;70,000 + Benefits | 🌍 Hybrid Working
 
 
 
 
 
 Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale.
 
 
 
 
 
 Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services.
 
 
 
 
 
 This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact.
 
 
 
 
 
 ⚙️ Tech Stack:
 
 
 Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows
 
 
 
 
 
 🚀 About the Role:
 
 
 
 
 <ul>
 <li>
 As a Machine Learning Engineer, you will:
 </li>
 <li>
 Develop, train, and optimise machine learning models focused on computer vision and generative AI applications
 </li>
 <li>
 Build and deploy scalable ML solutions into production environments
 </li>
 <li>
 Design automation solutions that reduce manual effort and improve operational efficiency
 </li>
 <li>
 Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy
 </li>
 <li>
 Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions
 </li>
 <li>
 Research emerging technologies and rapidly evaluate their suitability for business applications
 </li>
 <li>
 Contribute to the evolution of production-grade machine learning infrastructure and workflows
 </li>
 </ul>
 
 
 
 
 ➕ Nice to Have:
 
 
 
 
 <ul>
 <li>
 Several years of hands-on experience within machine learning and computer vision
 </li>
 <li>
 Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow
 </li>
 <li>
 Practical experience working with generative AI technologies including diffusion models and GANs
 </li>
 <li>
 Understanding of ML deployment, scalability, performance optimisation, and production environments
 </li>
 <li>
 Experience with Docker and cloud-based infrastructure
 </li>
 <li>
 Knowledge of creative AI tools and visual content workflows
 </li>
 <li>
 Experience working with image-based products, digital content platforms, or related industries
 </li>
 <li>
 Strong analytical thinking combined with a pragmatic, solution-oriented mindset
 </li>
 <li>
 Ability to communicate effectively in an international and cross-functional environment
 </li>
 </ul>
 
 
 
 
 💪 Benefits:
 
 
 
 
 <ul>
 <li>
 Opportunity to work on cutting-edge AI and machine learning technologies
 </li>
 <li>
 Highly collaborative and innovative working environment
 </li>
 <li>
 Flexible working arrangements with hybrid options
 </li>
 <li>
 Exposure to challenging technical problems with real-world impact
 </li>
 <li>
 Professional development support, training, and continuous learning opportunities
 </li>
 <li>
 Modern working environment with strong team culture and regular social activities
 </li>
 </ul>
 
 
 
 
 
 ✉️ Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.
 
 
</div>

Machine Learning Engineer

Mercor

<div>
 
 About The Job
 
 
 
 
 Mercor
 
 connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
 
 Benchmark
 
 ,
 
 General Catalyst
 
 ,
 
 Peter Thiel
 
 ,
 
 Adam D'Angelo
 
 ,
 
 Larry Summers
 
 , and
 
 Jack Dorsey
 
 .
 
 
 
 Position:
 
 ML Engineer (Coding Agent Experience)
 
 
 
 Type:
 
 
 Contract
 
 
 
 
 Compensation:
 
 
 $85/hour
 
 
 
 
 Location:
 
 
 Remote
 
 
 
 
 Role Responsibilities
 
 
 
 <ul>
 <li>
 Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
 </li>
 <li>
 Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
 </li>
 <li>
 Identify bugs, edge cases, performance issues, and failure modes in AI models.
 </li>
 <li>
 Compare outputs from multiple frontier models and assess their strengths and weaknesses.
 </li>
 <li>
 Apply professional engineering judgment to realistic ML engineering scenarios.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Must-Have
 
 
 
 <ul>
 <li>
 2+ years of professional machine learning engineering experience.
 </li>
 <li>
 Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
 </li>
 <li>
 Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
 </li>
 <li>
 Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
 
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience deploying ML systems to production.
 
 
 
 </li>
 </ul>
 
 Compensation &amp; Legal
 
 
 
 <ul>
 <li>
 $400 per accepted task
 </li>
 <li>
 Compensation is tied to accepted work.
 
 
 
 </li>
 </ul>
 
 Application Process (Takes 20&ndash;30 mins to complete)
 
 
 
 <ul>
 <li>
 Upload resume
 </li>
 <li>
 AI interview based on your resume
 </li>
 <li>
 Submit form
 
 
 
 </li>
 </ul>
 
 Resources &amp; Support
 
 
 
 <ul>
 <li>
 For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
 </li>
 <li>
 For any help or support, reach out to: support@mercor.com
 
 
 
 </li>
 </ul>
 
 PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 
</div>

AI/ML Engineer - Fully Remote | Upto $85/hr

NexTexAI

<div>
 
 NexTex AI is a Berlin-based deep-tech startup building an AI-powered intelligence layer for textile manufacturing.
 
 
 
 Our platform combines industrial cameras, retrofit sensors, PLC/SCADA signals, edge computing and artificial intelligence to detect textile defects, optimize production processes and generate sustainability KPIs for CSRD and EU Green Deal compliance.
 
 
 
 We are currently preparing our EXIST Startup Grant application and a ProFIT Berlin R&amp;D funding application. Our goal is to build and validate an MVP with pilot textile manufacturers during the first year and scale into one of Europe's leading industrial AI platforms for textile production.
 
 
 
 We are looking for a Founding Software Engineer who wants to join the founding team and help build the technical backbone of the company from day one.
 
 
 Tasks
 
 
 As a Founding Software Engineer, you will be responsible for designing and building the backend systems, cloud infrastructure and AI deployment architecture behind NexTex AI.
 
 
 
 You will work closely with the founders, machine learning engineers and future computer vision engineers to create a scalable edge-to-cloud platform for industrial AI applications.
 
 
 
 Your responsibilities include:
 
 
 
 &bull; Building cloud-native infrastructure and deployment pipelines
 
 
 
 &bull; Designing and developing scalable backend services and APIs
 
 
 
 &bull; Building dashboards, analytics systems and internal tools
 
 
 
 &bull; Developing industrial data pipelines for machine, sensor and camera data
 
 
 
 &bull; Supporting edge-to-cloud communication and industrial integrations
 
 
 
 &bull; Supporting AI model deployment, monitoring and inference workflows
 
 
 
 &bull; Structuring textile production data, defect classifications and sustainability KPIs
 
 
 
 &bull; Working directly with pilot factories and industrial partners
 
 
 
 &bull; Contributing to product architecture and technical strategy
 
 
 Requirements
 
 
 Strong software engineering background
 
 
 
 &bull; Strong Python and C++ programming skills
 
 
 
 &bull; Experience with FastAPI, Django, Flask, Node.js or similar frameworks
 
 
 
 &bull; Experience with PostgreSQL or similar database systems
 
 
 
 &bull; Experience with Docker and containerized environments
 
 
 
 &bull; Experience with AWS, Azure or Google Cloud
 
 
 
 &bull; Understanding of REST APIs and scalable software architectures
 
 
 
 &bull; Fluent English
 
 
 
 &bull; Ability to work independently in an early-stage startup environment
 
 
 
 Preferred Qualifications
 
 
 
 &bull; Located in Berlin or willing to relocate to Berlin
 
 
 
 &bull; Professional working proficiency in German (prior work experience in a German-speaking environment preferred)
 
 
 
 &bull; Experience with Computer Vision and Machine Learning systems (using frameworks such as PyTorch, TensorFlow or ONNX)
 
 
 
 &bull; Experience with MLOps and model deployment pipelines
 
 
 
 &bull; Experience with Edge AI deployments (NVIDIA Jetson, CUDA or TensorRT)
 
 
 
 &bull; Experience with Industrial IoT, PLC/SCADA systems or manufacturing environments
 
 
 
 &bull; Startup or founding-team experience
 
 
 
 &bull; Interest in textile manufacturing, sustainability and Industry 4.0
 
 
 Benefits
 
 
 &bull; 10% equity participation as a founding team member
 
 
 
 &bull; Approx. &euro;2,500/month through the German Federal EXIST Startup Grant during the first year
 
 
 
 &bull; Significant compensation increase planned following successful MVP validation and funding milestones
 
 
 
 &bull; Opportunity to build a deep-tech startup from day one
 
 
 
 &bull; Direct impact on product, technology and company strategy
 
 
 
 &bull; Access to real industrial production environments and pilot textile factories
 
 
 
 &bull; Work on AI, Computer Vision, Edge AI, Industrial IoT and Sustainability Intelligence
 
 
 
 &bull; Direct collaboration with experienced founders, academic advisors and industry partners
 
 
 
 &bull; Startup coaching, legal support and mentoring through EXIST and ProFIT Berlin
 
 
 
 &bull; Opportunity to shape both the product and company from an early stage
 
 
 
 &bull; Flexible working environment
 
 
 
 &bull; Potential CTO-level growth opportunities as the company scales
 
 
 
 We are looking for ambitious engineers who want to build something meaningful from the ground up. If you are excited about AI, industrial systems, sustainability and entrepreneurship, we would love to hear from you.
 
 
 
 To apply, please submit:
 
 
 
 &bull; Your CV
 
 
 
 &bull; LinkedIn profile
 
 
 
 &bull; A short introduction explaining why you are interested in joining NexTex AI
 
 
 
 Selected candidates will be invited to:
 
 
 
 1. Introductory discussion with the founders
 
 
 
 2. Technical discussion and architecture review
 
 
 
 3. Final founder meeting
 
 
 
 If successful, you will join NexTex AI as a founding team member with 10% equity and play a key role in building the future of industrial AI for textile manufacturing.
 
 
 
 We look forward to hearing from you.
 
</div>

Founding Software Engineer (Backend, Cloud & AI Infrastructure)

Cresta

<div>
 Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta&rsquo;s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world&rsquo;s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.
 
 
 Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world&rsquo;s leading investors, including a16z, Greylock, and Sequoia. Cresta&rsquo;s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu, founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.
 
 
 Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.
 
 
 
 About The Role
 
 
 
 As a Senior full-stack engineer, with a backend focus, you will be at the forefront of shaping the future of customer engagement! As we work towards our vision, you'll be instrumental in delivering timely, actionable insights that drive business growth from day one. We're building a state-of-the-art Customer Data Platform, visualizing relevant insights for businesses post-onboarding and guiding customer engagement across all touch-points. Be part of the team that's redefining the way businesses connect with their customers!
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and maintain backend services and APIs to support applications.
 </li>
 <li>
 Build and optimize data storage solutions using Postgres, ClickHouse and Elasticsearch to ensure high performance and scalability.
 </li>
 <li>
 Collaborate with cross-functional teams, including frontend engineers, data scientists, and machine learning engineers, to deliver end-to-end solutions.
 </li>
 <li>
 Monitor and troubleshoot performance issues in distributed systems and databases.
 </li>
 <li>
 Write clean, maintainable, and efficient code following best practices for backend development.
 </li>
 <li>
 Participate in code reviews, testing, and continuous integration efforts.
 </li>
 <li>
 Ensure security, scalability, and reliability of backend services.
 </li>
 <li>
 Analyze and improve system architecture, focusing on performance bottlenecks, scaling, and security.
 
 
 </li>
 </ul>
 
 Qualifications We Value
 
 
 
 <ul>
 <li>
 Proven experience as a Backend Engineer with a focus on database design and system architecture.
 </li>
 <li>
 Strong expertise in ClickHouse or similar columnar databases for managing large-scale, real-time analytical queries.
 </li>
 <li>
 Hands-on experience with Elasticsearch for indexing and searching large datasets.
 </li>
 <li>
 Proficient in backend programming languages such as Python, Go.
 </li>
 <li>
 Experience with RESTful API design and development.
 </li>
 <li>
 Solid understanding of distributed systems, microservices architecture, and cloud infrastructure.
 </li>
 <li>
 Experience with performance tuning, data modeling, and query optimization.
 </li>
 <li>
 Strong problem-solving skills and attention to detail.
 </li>
 <li>
 Excellent communication and teamwork abilities.
 
 
 </li>
 </ul>
 
 Perks &amp; Benefits
 
 
 
 <ul>
 <li>
 Paid parental leave to support you and your family
 </li>
 <li>
 Monthly Health &amp; Wellness allowance
 </li>
 <li>
 Work from home office stipend to help you succeed in a remote environment
 </li>
 <li>
 Lunch reimbursement for in-office employees
 </li>
 <li>
 PTO: 28 days in Germany
 
 
 </li>
 </ul>
 Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. Your recruiter can provide further details.
 
 
 We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai
</div>

Senior Software Engineer, Backend (Berlin)

Zeta Global

<div>WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. 


The Role

We&rsquo;re looking for a skilled ML Engineer / Data Scientist with 3+ years of software or applied ML experience to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on AWS.This role sits at the intersection of data science and engineering: exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure. 

<div>
Who you are:
<ul>
<li>Strong foundation in machine learning, statistics and experiment design.</li>
<li>Experience building models for real business or product problems, not only academic benchmarks.</li>
<li>Comfortable working with structured and unstructured data: feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.</li>
<li>Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).</li>
<li>Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, prompt/versioning).</li>
<li>Proficient in Python and able to write clean, modular, testable code.</li>
<li>Experience developing and deploying ML solutions in a cloud environment, especially AWS.</li>
<li>Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.</li>
<li>Independent engineer who can own work from problem framing experimentation implementation rollout.</li>
<li>Excellent written and spoken English.</li>
<li>Enjoy working closely with engineers, product partners, and other data scientists.</li>
<li>Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.</li>
<li>Master&rsquo;s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience.</li>
</ul>
Nice to have:
<ul>
<li>Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks.</li>
<li>Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&amp;B).</li>
<li>Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or Spark.</li>
<li>Exposure to feature stores, embedding pipelines, or vector search for retrieval-based systems.</li>
<li>Experience building HTTP/gRPC APIs or lightweight services around model inference.</li>
<li>Working knowledge of Docker, basic orchestration, and CI/CD (e.g. GitLab CI).</li>
<li>Experience in agile, remote and async team environments.</li>
<li>Publications, patents, Kaggle/competition results, or open-source ML contributions.</li>
</ul>
What you might like about this role:
<ul>
<li>Hands-on modeling work with room to explore, benchmark, and improve real systems.</li>
<li>Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings.</li>
<li>A multicultural, engineering-focused team with strong peer support.</li>
<li>High trust and autonomy&mdash;clear goals, freedom in how to reach them.</li>
<li>Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets.</li>
<li>Short approval cycles and solid product partnership.</li>
<li>A healthy meeting policy and emphasis on protecting focus time.</li>
<li>Flexible hours, remote/home office options, and a calm, engineers-only office when on-site.</li>
<li>Competitive compensation, including stock options.</li></ul> 
<div>
</div><div></div><div><div>We&rsquo;re hiring across multiple levels. Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.

We&rsquo;re especially interested in candidates who are technically strong, intellectually curious, and motivated by difficult, ambiguous problems where good data science and solid engineering both matter. 


PEOPLE &amp; CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.
We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 


#LI-NP1</div></div></div></div>

ML Ops Engineer

<div>
 
 &nbsp;
 
 
 
 WHO WE ARE&nbsp;
 
 
 
 Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
 
 
 &nbsp;
 
 
 
 The Role
 
 
 
 We&rsquo;re looking for a skilled&nbsp;
 
 ML Engineer / Data Scientist
 
 &nbsp;with&nbsp;
 
 3+ years of software or applied ML experience
 
 &nbsp;to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on&nbsp;
 
 AWS
 
 .This role sits at the intersection of&nbsp;
 
 data science and engineering
 
 : exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure.
 
 
 &nbsp;
 
 
 
 Who you are:
 
 
 <ul>
 <li>
 Strong foundation in&nbsp;
 
 machine learning,&nbsp;statistics
 
 and&nbsp;
 
 experiment design
 
 .
 </li>
 <li>
 Experience building models for&nbsp;
 
 real business or product problems
 
 , not only academic benchmarks.
 </li>
 <li>
 Comfortable working with&nbsp;
 
 structured and unstructured data
 
 : feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
 </li>
 <li>
 Able to compare approaches with clear&nbsp;
 
 metrics
 
 , error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
 </li>
 <li>
 Interest in&nbsp;
 
 modern ML
 
 , including classical ML, deep learning, and&nbsp;
 
 LLM / GenAI workflows
 
 &nbsp;where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
 </li>
 <li>
 Proficient in&nbsp;
 
 Python
 
 &nbsp;and able to write&nbsp;
 
 clean, modular, testable&nbsp;code
 
 .
 </li>
 <li>
 Experience developing and deploying ML solutions in a&nbsp;
 
 cloud environment
 
 , especially&nbsp;AWS.
 </li>
 <li>
 Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
 </li>
 <li>
 Independent engineer who can own work from&nbsp;
 
 problem framing &rarr; experimentation &rarr; implementation &rarr; rollout
 
 .
 </li>
 <li>
 Excellent&nbsp;
 
 written and spoken English
 
 .
 </li>
 <li>
 Enjoy working closely with engineers, product partners, and other data scientists.
 </li>
 <li>
 Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
 </li>
 <li>
 
 Master&rsquo;s degree
 
 &nbsp;in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar),&nbsp;
 
 or equivalent practical experience
 
 .
 </li>
 </ul>
 
 
 Nice to have:
 
 
 <ul>
 <li>
 Experience with&nbsp;
 
 scikit-learn,&nbsp;PyTorch,&nbsp;TensorFlow,&nbsp;XGBoost
 
 , or similar modeling stacks.
 </li>
 <li>
 Familiarity with&nbsp;
 
 ML experiment tracking
 
 &nbsp;and reproducibility (e.g. MLflow, W&amp;B).
 </li>
 <li>
 Experience with&nbsp;
 
 SQL
 
 , data warehouses/lakes, and pipeline tools such as&nbsp;
 
 Airflow,&nbsp;dbt, or&nbsp;Spark
 
 .
 </li>
 <li>
 Exposure to&nbsp;
 
 feature stores
 
 , embedding pipelines, or&nbsp;
 
 vector search
 
 &nbsp;for retrieval-based systems.
 </li>
 <li>
 Experience building&nbsp;
 
 HTTP/gRPC APIs
 
 &nbsp;or lightweight services around model inference.
 </li>
 <li>
 Working knowledge of&nbsp;
 
 Docker
 
 , basic orchestration, and CI/CD (e.g.&nbsp;
 
 GitLab CI
 
 ).
 </li>
 <li>
 Experience in&nbsp;
 
 agile
 
 ,&nbsp;
 
 remote
 
 and&nbsp;
 
 async
 
 &nbsp;team environments.
 </li>
 <li>
 Publications, patents, Kaggle/competition results, or open-source ML contributions.
 </li>
 </ul>
 
 
 What you might like about this role:
 
 
 <ul>
 <li>
 
 Hands-on modeling work
 
 &nbsp;with room to explore, benchmark, and improve real systems.
 </li>
 <li>
 Collaboration on&nbsp;
 
 ML patent submissions
 
 &nbsp;and participation in&nbsp;weekly ML / research paper review&nbsp;meetings.
 </li>
 <li>
 A&nbsp;
 
 multicultural, engineering-focused team
 
 &nbsp;with strong peer support.
 </li>
 <li>
 
 High trust and autonomy
 
 &mdash;clear goals, freedom in how to reach them.
 </li>
 <li>
 
 Internal product impact
 
 : meaningful projects that improve developer and user experience, not endless maintenance tickets.
 </li>
 <li>
 
 Short approval cycles
 
 &nbsp;and solid product partnership.
 </li>
 <li>
 A&nbsp;
 
 healthy meeting policy&nbsp;
 
 and emphasis on protecting focus time.
 </li>
 <li>
 
 Flexible hours
 
 , remote/home office options, and a calm, engineers-only office when on-site.
 </li>
 <li>
 
 Competitive compensation
 
 , including&nbsp;stock options.
 </li>
 </ul>
 &nbsp;
 
 We&rsquo;re hiring across
 
 multiple levels
 
 . Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.
 
 
 We&rsquo;re especially interested in candidates who are&nbsp;
 
 technically strong, intellectually curious, and motivated by difficult, ambiguous problems
 
 &nbsp;where good data science and solid engineering both matter.
 
 
 &nbsp;
 
 
 &nbsp;
 
 
 
 PEOPLE &amp; CULTURE AT ZETA
 
 
 
 Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.&nbsp;&nbsp;
 
 
 We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:&nbsp; https://zetaglobal.com/blog/a-look-into-zetas-ergs/&nbsp;
 
 
 
 ZETA IN THE NEWS!
 
 
 
 https://zetaglobal.com/press/?cat=press-releases&nbsp;
 
 
 &nbsp;
 
 
 
 
 
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