learning engineer

CLUSTOR COMPUTING

Job SummaryWe are looking for a data-driven Machine Learning Engineer to join our AI team. In this role, you will bridge the gap between data science and software engineering by building, deploying, and maintaining scalable machine learning models. As a junior member of the team, you will work closely with senior engineers to transform raw data into intelligent features and predictive systems. This is an ideal position for a recent graduate or early-career professional who is passionate about AI and eager to solve real-world problems through automation and predictive analytics.Key Responsibilities&middot;Model Development &amp; Training: Assist in the design and implementation of ML models (Supervised, Unsupervised, and Deep Learning) using frameworks like PyTorch or TensorFlow.&middot;Data Preprocessing: Build and maintain data pipelines to clean, normalize, and transform raw data into high-quality features for model training.&middot;Model Evaluation: Use statistical metrics (Accuracy, Precision/Recall, F1-score, RMSE) to evaluate model performance and perform hyperparameter tuning to optimize results.&middot;Deployment (MLOps): Collaborate with the engineering team to containerize models (Docker) and deploy them into production environments (AWS/Azure/GCP).&middot;Monitoring &amp; Maintenance: Monitor deployed models for performance degradation (data drift) and perform periodic retraining to ensure continued accuracy.&middot;Research &amp; Documentation: Stay updated with the latest AI research and document the development lifecycle, from experiment results to production workflows.&middot;Cross-functional Collaboration: Work with Data Scientists to understand business requirements and with Software Engineers to integrate ML models into end-user applications.Job Types: Full-time, Permanent, FresherPay: ₹120,000.00 - ₹350,000.00 per yearWork Location: In person

Machine Learning Engineer

Aarki

<div>
 
 Who are we?
 
 
 
 Aarki 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.
 
 
 
 The role?
 
 
 
 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.
 
 
 
 What will you do?
 
 
 
 <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>
 
 What are we looking for?
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Mathematics, Physics, Computer Science, or a related technical field.
 </li>
 <li>
 At least 2 years 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>
 Nice-to-Have
 
 
 <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>

ML Bench

Job DescriptionWe are seeking a skilled AI/ML Engineer with 2+ years of hands-on experience in building, deploying, and optimizing machine learning models. The candidate should be able to translate business problems into scalable AI solutions and work collaboratively with cross-functional teams.Key Responsibilities<ul><li>Design, develop, and deploy ML models for real-world applications</li><li>Perform data preprocessing, feature engineering, and model evaluation</li><li>Implement algorithms (regression, classification, clustering, etc.)</li><li>Optimize model performance and accuracy</li><li>Build and maintain data pipelines for ML workflows</li><li>Deploy models via APIs or cloud platforms</li><li>Monitor, retrain, and maintain models in production</li><li>Collaborate with product, engineering, and data teams</li></ul>Required Skills<ul><li>Strong proficiency in Python</li><li>Hands-on experience with TensorFlow, PyTorch, or Scikit-learn</li><li>Experience with Pandas, NumPy, and data handling</li><li>Solid understanding of statistics and ML fundamentals</li><li>Experience in model deployment and REST APIs</li><li>Familiarity with AWS, GCP, or Azure</li><li>Version control experience (Git)</li></ul>Preferred<ul><li>Experience in Deep Learning, NLP, or Computer Vision</li><li>Knowledge of MLOps practices</li><li>Experience with Docker or Kubernetes</li><li>Exposure to Agile environments</li></ul>Perks &amp; Benefits:<ul><li>Travel Allowance</li><li>Birthday gifts</li><li>Opportunities to learn and grow with a skilled team.</li><li>Market-competitive salary.</li><li>Annual Dinners</li></ul>Job: Full-Time Timings: 9 AM to 6 PM Working Days: Monday to Friday Budget: PKR 120k to 180k Location: ML Bench, 424, J3 Johar Town, Lahore<ul><li>Join ML Bench by sending your resume here hr@ml-bench.com</li></ul>Job Type: Full-timePay: Rs120,000.00 - Rs180,000.00 per monthApplication Question(s):<ul><li>What is Your Current Salary?</li><li>What is your Expected Salary?</li><li>This is an on-site position apply only if you are residing in Lahore?</li><li>Apply only if you can attend an on-site interview?</li></ul>Work Location: In person

<div>At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we&rsquo;ll give you what you need to make it happen. It won&rsquo;t always be easy, growing takes grit. But at ABB, you&rsquo;ll never run alone. Run what runs the world.
This Position reports to:
Senior Machine Learning Engineer 
What we believe in
Our mission in ABB IS (Information Systems) is to use information technology to provide valuable, reliable, and competitive IS services for ABB. If you offer deep technical experience, a methodical approach to solving problems, and the willingness to help us remain competitive, we want you on our team.
Your role and responsibilities
Own the stability, scalability, and performance of production-grade ML platforms by designing and enhancing backend services, orchestration layers, and system integrations that power critical ML workflows. Ensure resilient system architectures in distributed settings to preserve high availability, tolerate faults, and enable smooth operation. Own complex problem resolution and perform in-depth root-cause analysis across application, data, and infrastructure layers to reduce operational risk and downtime. Advocate for reliable deployment and DevOps workflows using Docker, Kubernetes (AKS), and CI/CD, ensuring configuration and release controls are applied. Act as a senior technical anchor for cross-functional teams and external vendors, translating complex ML and business requirements into resilient, scalable backend solutions.
The work model for the role is: Hybrid
You will be mainly accountable for:<ul><li>
Oversee the design, improvement, and ownership of backend services that support ML workflows (model registry, deployments, APIs), ensuring well-architected systems across service boundaries, data flow, scalability, fault tolerance, performance, and maintainability, while advising internal teams and vendors on architecture.</li><li>
Diagnose and fix complex production incidents involving Spark jobs, Airflow pipelines, Azure ML runs, and AKS services through in-depth root-cause analysis across application, infrastructure, data, and configuration layers, while enhancing reliability, observability, and deployment stability.</li><li>
Design and maintain Dockerized services and Kubernetes (AKS) deployments, contribute to CI/CD pipelines, and establish best practices for configuration management, secrets handling, environment isolation, scaling strategies, upgrades, and rollback mechanisms.</li><li>
Serve as the primary technical contact, working with data scientists, ML engineers, business analysts, platform teams, and external vendors to convert business and ML workflow needs into scalable backend architectures, while coaching less experienced engineers on system design and complex debugging techniques.</li></ul>
Qualifications for the role:<ul><li>
3&ndash;5 years of experience as a Backend Engineer, Platform Engineer, Senior ML Engineer, or in a similar role.</li><li>
Demonstrated backend development skills in Python (or Java/Go) with direct experience creating APIs and services.</li><li>
Robust understanding of system design, covering distributed systems, microservices, scalability, fault tolerance, and reliability.</li><li>
Direct experience with AML and Airflow focused on platform or operational responsibilities.</li><li>
Working knowledge of Azure ML pipelines, endpoints, and deployment patterns.</li><li>
Solid practical experience with Docker and Kubernetes (AKS).</li><li>
Ability to identify and resolve complex production issues across application, data, and infrastructure layers.</li></ul> 
More about us
At ABB IS (Information Systems), our mission is to apply information technology to deliver secure, reliable, and competitive digital solutions that create measurable value for ABB. Our commitment is to advance innovation, operational efficiency, and responsive business processes via reliable technical capabilities and strategic execution. If you possess deep technical capability, clear problem-solving skills, and the commitment to support our advancement in a rapidly developing landscape, we welcome you aboard 
 
We value people from different backgrounds. Could this be your story? Apply today or visit www.abb.com to read more about us and learn about the impact of our solutions across the globe.
Fraud Warning: Any genuine offer from ABB will always be preceded by a formal application and interview process. 
We never ask for money from job applicants.
For current open positions you can visit our career website https://global.abb/group/en/careers and apply.
Please refer to detailed recruitment fraud caution notice using the link https://global.abb/group/en/careers/how-to-apply/fraud-warning.</div>

Apple

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn&rsquo;t have imagined, and now, can&rsquo;t imagine living without. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do. 
 
Description 
 
APPLE INC has the following available in Cambridge, Massachusetts. Engage with research teams to map out technology roadmaps including external partners like AWS. Write software to incorporate the latest developments in open-source Machine Learning technology and make it accessible to speech researchers at Apple. Lead weekly syncs with research and engineering teams on challenges and future directions. Mentor engineers and researchers on best software engineering practices through code reviews and discussions. Scope out, plan, and lead major software engineering features with a one-year time horizon. Lead weekly meetings with multiple contributors and stakeholders to ensure project stays on track. Leverage deep understanding of Software Engineering, Machine Learning, and Speech Processing to suggest new directions to take to leadership and partner teams. Make technical recommendations and help team implement Machine Learning tools and pipelines that incorporate best practices for preserving customer privacy during training and evaluation of speech recognition models. Work with partner teams to troubleshoot and fix tools and infrastructure used by speech researchers to unblock work and serve as a technical liaison between multiple engineering teams at Apple and Speech Recognition researchers. 40 hours/week. 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 $162,500 - $244,600/yr and your base pay will depend on your skills, qualifications, experience, and location. 
 
PAY &amp; BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;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&rsquo;s Employee Stock Purchase Plan. You&rsquo;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: https://www.apple.com/careers/us/benefits.html. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 
 
Preferred Qualifications 
 
N/A 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree or foreign equivalent in Computer Science, Computer Engineering, Software Engineering, Machine Learning or related field and 1 year of experience in the job offered or related occupation. 
 
1 year of experience with each of the following skills is required: 
 
Applying Machine Learning and Artificial Concepts including neural networks, conformers, and transformers to improve speech recognition models 
 
Using Machine Learning toolkits, including PyTorch and experience optimizing models for faster computation. 
 
Leveraging GPUs in distributed workloads for machine learning tasks to train large, highly accurate machine learning models while using GPU resources efficiently to allow more research ideas and improve models for customers faster 
 
Utilizing Python for software engineering tasks. 
 
Managing large Python codebase with more than ten contributors. 
 
Managing machine learning projects with interdisciplinary teams including researchers, engineers, and linguists to improve models for customers. 
 
Using speech understanding and speech concepts for all products and languages including a variety of acoustic environments and accents. 
 
Utilizing technical knowledge and distilling requirements to work with infrastructure partner teams internally and externally. 
 
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 .

Liftoff

<div><div>Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand.

Liftoff's solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence.</div>
About the Revenue Engine team

The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for Liftoff and its advertisers.

As a Machine Learning Engineer on the Revenue Engine team, you will:
<ul>
<li>Build statistical models and production systems to balance advertiser performance with business goals.</li>
<li>Tune optimization parameters, measure internal competition, and model dynamic environments.</li>
<li>Design and run experiments to validate theories underpinning the mobile ad tech economy.</li>
<li>Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations.</li>
<li>Collaborate with a team of world-class engineers with diverse backgrounds as well as peers across the broader company (e.g. Operations, GTM).</li>
<li>Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences.</li>
<li>Be part of an &quot;engineering excellence&quot; culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review.</li>
</ul>
Requirements:
<ul>
<li>PhD in Computer Science, Machine Learning, Economics, or a related field.</li>
<li>Industry experience applying economics or machine learning to large scale problems.</li>
<li>Solid engineering and coding skills.</li>
<li>Excellent team communication and collaboration skills.</li>
<li>Experience with ad tech is a solid plus.</li>
</ul>
Location: 
This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, TX, UT, and WA.

We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City.

Travel Expectations: 
We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building.

#LI-EL1

#LI-REMOTE

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process, we provide Covey with job requirements and candidate-submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

Please see the independent bias audit report covering our use of Covey here.<div>
Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We're shaping the future of the mobile app ecosystem&mdash;join us and help accelerate what's next. 


Liftoff's compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence. 


Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law.

Agency and Third Party Recruiter Notice:

Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System.</div></div>

The Home Depot

<div><div>Position Purpose:
The Staff Software Engineer is responsible for leading a team of engineers building and designing a product that our customers and associates love. As a Staff Software Engineer, you will be part of a dynamic team with engineers of all experience levels who help each other build and grow technical and leadership skills while creating, deploying, and supporting production applications. In this role, you will also provide technical leadership on machine learning systems, including model development, production deployment, monitoring, and lifecycle management of ML solutions operating at scale. In addition, Staff Software Engineers will assist in product and tool selection, configuration, security, resilience, performance tuning and production monitoring. 
Staff Software Engineers contribute to foundational code elements that can be reused as well as architectural diagrams and other product-related documentation. You will help define best practices for building reliable, explainable, and maintainable ML systems that integrate seamlessly with broader software platforms. 
As a Staff Software Engineer, you will be a core player on the product team and are expected to build and grow the skillsets of the more junior Engineers. 
Key Responsibilities:<ul><li>
45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate</li><li>
20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
3 - 6 years of relevant work experience</li><li>
Strong experience designing, training, evaluating, and deploying machine learning models in production environments, including batch and real-time inference systems</li><li>
Experience with ML lifecycle management, including feature engineering, model versioning, experimentation, validation, and monitoring for data drift and model performance degradation</li><li>
Experience building and operating ML pipelines using cloud-native services, data platforms, and CI/CD practices for reproducible and reliable model deployment</li><li>
Strong understanding of applied statistics, model evaluation metrics, and tradeoffs between model accuracy, interpretability, latency, and operational cost</li><li>
Experience with algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Experience in training machine learning models with extremely large datasets</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc. - and experience integrating them into scalable software systems</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Experience in cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Experience in defensive coding practices and patterns for high Availability</li><li>
Experience in A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div> 
Apply End Date: 04/01/2026</div>

Staff Machine Learning Engineer

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