machine learning infrastructure engineer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree or equivalent practical experience.</li>
<li>8 years of experience in software development.</li>
<li>5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.</li>
<li>5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li>
<li>2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).</li>
<li>Experience with software development in one or more general purpose programming languages (e.g., Java, C/C++, or Go, etc.).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field.</li>
<li>8 years of experience with data structures and algorithms.</li>
<li>3 years of experience in a technical leadership role leading project teams and setting technical direction.</li>
<li>Experience with shipping 0-to-1 AI applications, with a holistic understanding of product, quality, and infra.</li>
<li>Knowledge of data warehouses, big data, SQL, and data governance.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.<br>
<br>
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.</p>
<p>
Knowledge Catalog is the foundational context engine for the AI era designed as always-on enterprise-wide catalog for AI, it serves as the single reliable source of truth for both human users and AI agents. By bridging the gap between raw data and true business meaning, we power Google's Agentic Data Cloud (demoed at Google Cloud Next 26 - Agentic Data Cloud), enabling AI agents to reason, act, and execute on enterprise data. It provides universal business context and governance for your entire data estate. Data teams and AI developers use Knowledge Catalog to discover data, enforce policies, and retrieve context for both analytics and self-sustaining applications.</p>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
<br>
<br>
US: $262000 - $365000 (USD) + 25% bonus target + equity + benefits<br>
<br>
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Generate critical ideas and own the architectural direction for highly ambiguous problem spaces. Maintain a direct approach to coding and system design while setting the standard for engineering excellence.</li>
<li>Act as a technical multiplier. Navigate complex organizational structures to influence technical decisions and align outcomes across various Google Cloud products and distinct engineering organizations.</li>
<li>Apply strong product-thinking to technical issues. Partner closely with engineering and product managers to define the long-term roadmap and ensure our technical capabilities align with customer and business needs.</li>
<li>Provide technical guidance, mentorship, and leadership to engineers across the team, elevating the overall capability and velocity of the organization.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Staff Software Engineer, Knowledge Catalog For AI

Smvsoft LLC

<p><b>Founding Engineer - Applied AI</b><br/>San francisco, CA (Full time)- In-Office</p><p>$180k-$230k per annum</p><p><b>NO C2C</b></p><p><b>About the Role</b></p><p>Hiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.</p><p>This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.</p><p><b>Key Responsibilities</b></p><ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul><p><b>Requirements</b></p><p><b>Must-Have</b></p><ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul><p><b>Nice-to-Have</b></p><ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul><p>Pay: $180,000.00 - $230,000.00 per year</p><p>Work Location: In person</p>

Founding Engineer - Applied AI

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .</div><p>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live</p><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
[Expert Level Focus] Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles.</li><li>
a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred.</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-AV3</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3618</div>
</div><div><div>Job Category</div>
<div>Data Science and Machine Learning</div>
</div><div><div>Posting Date</div>
<div>07/02/2026, 02:40 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>GB-Remote
</div></div>(Remote)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Envision Employment Solutions

<div><p><b>Envision Employment Solutions</b> is currently looking for a<b> Senior Data Scientist - AI &amp; ML Engineer </b>for one of our partners, a global leader in <b>consulting, digital transformation, technology and engineering services!</b></p><p></p><p><b>
About:</b></p><p>
The <b>Senior Data Scientist - AI &amp; ML Engineer </b>will be responsible for delivering end-to-end machine learning solutions, designing scalable AI architectures, and developing Agentic AI applications that drive intelligent automation and business value.</p><p></p><p><b>
Responsibilities:</b></p><p><b>
AI &amp; Machine Learning Development</b></p><ul><li>
Design, develop, and deploy AI and machine learning solutions that address business needs.
</li><li>Build and implement Agentic AI applications using modern AI frameworks.
</li><li>Lead the full machine learning lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
</li><li>Optimize models to improve accuracy, scalability, and performance in production environments.
</li><li>Implement model monitoring, drift detection, and retraining strategies.
</li></ul><p><b>Data Engineering &amp; MLOps</b></p><ul><li>
Design scalable data pipelines to support machine learning workloads.
</li><li>Collaborate with data engineers to ensure reliable data ingestion, transformation, and storage.
</li><li>Develop and maintain ML-focused CI/CD pipelines.
</li><li>Implement model versioning, automated testing, and deployment best practices.
</li><li>Support containerized and cloud-native ML deployments.
</li></ul><p><b>Cloud &amp; Solution Architecture</b></p><ul><li>
Design AI and ML solutions using cloud platforms such as Azure, AWS, or GCP.
</li><li>Architect scalable infrastructure to support enterprise AI applications.
</li><li>Recommend technology solutions aligned with business and technical requirements.
</li><li>Ensure AI solutions meet security, reliability, and performance standards.
</li></ul><p><b>Collaboration &amp; Leadership</b></p><ul><li>
Partner with business stakeholders to understand objectives and translate them into technical solutions.
</li><li>Collaborate with cross-functional teams throughout the solution lifecycle.
</li><li>Mentor junior data scientists and ML engineers.
</li><li>Promote best practices in machine learning, software engineering, and MLOps.
</li><li>Stay informed about emerging AI technologies and industry trends.</li></ul><br>
<b>
Requirements</b><br>
<ul><li>
6-10 years of experience working with complex datasets and solving real-world business problems using AI</li><li>
Proven track record of deploying and maintaining ML models in production environments and delivering AI solution architecture.</li><li>
Strong proficiency in Python, data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and agentic application development libraries (e.g. LangChain, LangGraph).</li><li>
Strong command of SQL and experience with large-scale data processing tools (e.g., Spark, Pandas).</li><li>
Deep understanding of cloud platforms (Azure, AWS, GCP) and their ML services.</li><li>
Skilled in MLOps practices including CI/CD, containerization (e.g. Docker), and orchestration (Kubernetes).</li><li>
Strong command of Git and collaborative development workflows.</li><li>
Excellent written and verbal communication skills, capable of conveying complex concepts to a variety of audiences.</li><li>
Fluent in Arabic &amp; English, both spoken and written (German is a plus!)</li><li>
Able to listen to and understand customer needs and articulate them as technical requirements to the team.</li><li>
Strong problem-solving abilities and attention to detail.</li><li>
Strategic thinking with the ability to align data science initiatives with business objectives.</li><li>
Strong leadership and team management skills with the ability to inspire and motivate.</li><li>
Ability to work collaboratively in a team environment.</li><li>
Self-motivated with a strong growth mindset.</li></ul></div>

Senior Data Scientist - AI & ML Engineer

HOMETRACK

<div><p>Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.</p><p>
At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs.</p><p></p><p>
Responsibilities:</p><ul><li>
Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.</li><li>
Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.</li><li>
Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.</li><li>
Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.</li></ul><p></p><p>
Requirements:</p><ul><li>
Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.</li><li>
Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.</li><li>
Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.</li><li>
Have worked with a cloud service, such as AWS.</li><li>
Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).</li><li>
Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.</li><li>
Comfortable working with Docker and containerised applications.</li><li>
Experience leveraging AI native engineering tooling.</li><li>
Passion for building products that meet customer needs and business objectives.</li><li>
Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Everyday Flex - greater flexibility over where and when you work</li><li>
25 days annual leave + extra days for years of service</li><li>
Day off for your birthday, house move, good deed day, and digital detox day</li><li>
Cycle to work and electric car schemes
</li><li>Free Calm App membership
</li><li>Enhanced Paternity Leave
</li><li>Fertility Treatment Financial Support
</li><li>Group Income Protection and private medical insurance</li><li>
Gym on-site in London &ndash; or membership in regional offices</li><li>
7.5% pension contribution by the company</li><li>
Discretionary annual bonus up to 10% of base salary</li><li>
Talent referral bonus up to &pound;5K</li></ul></div>

Senior Machine Learning Engineer

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Abaka AI

<div>
 <strong>
  About Abaka AI
  <br/>
  <br/>
 </strong>
 Abaka AI is built on one mission: to be the world&rsquo;s most trusted data partner for AI companies. More than 1,000 industry leaders across Generative AI, Embodied AI, and Automotive AI rely on us to power their data pipelines. With our headquarters in Silicon Valley&mdash;and teams in Paris, Singapore, and Tokyo&mdash;we support global partners with fast, reliable, and scalable data solutions.
 <br/>
 <br/>
 Our offerings include a diverse catalog of off-the-shelf datasets (image, video, multimodal, reasoning, 3D, and beyond) as well as comprehensive data collection and annotation services. Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring our first Machine Learning Engineer in the United States, a foundational role that will shape how Abaka builds, trains, and optimizes multimodal AI systems. You will own the design and development of scalable training pipelines, work directly with our data engineering and research teams, and help drive the technical roadmap for model development across multiple modalities.
 <br/>
 <br/>
 As an early member of the engineering team, you will influence core decisions around model training strategy, experimentation frameworks, distributed infrastructure, and internal best practices. Your work will directly impact the performance of frontier models trained on Abaka datasets and will help elevate the technical bar for our clients and partners.
 <br/>
 <br/>
 If you thrive in high-ownership environments and want to shape the machine learning foundation of a fast-moving AI company, this role offers an opportunity to make an immediate and lasting impact.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data.
  </li>
  <li>
   Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration.
  </li>
  <li>
   Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance.
  </li>
  <li>
   Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment.
  </li>
  <li>
   Identify and address performance bottlenecks in data or training pipelines to improve throughput, stability, and resource utilization.
  </li>
  <li>
   Collaborate with product and infrastructure teams to ensure smooth integration of model outputs into both internal and client-facing applications.
  </li>
  <li>
   Support internal best practices for model governance, experiment tracking, and documentation to maintain high engineering standards and reproducibility.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong academic background in computer science, artificial intelligence, machine learning, or related fields. Master&rsquo;s degree or Ph.D. is preferred.
  </li>
  <li>
   3+ years of experience in applied machine learning or ML engineering, with a demonstrated ability to deliver production-ready models or pipelines.
  </li>
  <li>
   Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on experience in large-scale distributed training and inference systems.
  </li>
  <li>
   Familiarity with multimodal data processing (e.g., text-image pairing, video understanding, speech-audio modeling) and dataset optimization for model training.
  </li>
  <li>
   Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks.
  </li>
  <li>
   Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure).
  </li>
  <li>
   Excellent communication and collaboration skills, capable of working effectively across engineering, research, and product teams to accomplish shared goals.
  </li>
  <li>
   Self-driven and adaptable, comfortable operating in a fast-paced startup environment, and able to demonstrate strong ownership and urgency in execution.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation &amp; Benefits
  <br/>
  <br/>
 </strong>
 The base salary range for this position is $175,000 - $275,000 USD annually.
 <br/>
 <br/>
 Compensation may vary outside of this range depending on a number of factors, including a candidate&rsquo;s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI. This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).
</div>


Machine Learning Engineer

Search 3283+ Machine learning infrastructure engineer jobs near you this July. New roles added regularly across leading industries. Apply today.

3283 machine learning infrastructure engineer jobs Near Me

Senior Staff Software Engineer, Knowledge Catalog For AI

Founding Engineer - Applied AI

Expert Agentic AI Engineer

Senior Data Scientist - AI & ML Engineer

Senior Machine Learning Engineer

Expert Agentic AI Engineer

Machine Learning Engineer