learning engineer

IO DataLabs

IO Data Labs is hiring for a Machine Learning Engineer. we are Canada based Organization seeking for a candidate with strong technical background. Apply NowJob Title: Machine Learning EngineerLocation: RemoteTiming: 6:30pm-2:30amAbout the Role:2-3 years' experience in machine learning, deep learning, search, natural language processing, data science, or computer visionHands-on experience with Python programming.Develop and maintain machine learning models using Python.Collect and preprocess data for ML models.Train and evaluate models using Python libraries.Work on AI-driven applications, including predictive modeling, natural language processing, and computer vision (based on project requirements).Collaborate with cross-functional teams to understand business requirements and translate them into ML solutions.Solid understanding of machine learning algorithms (supervised, unsupervised, and reinforcement learning).Experience with libraries such as scikit-learn, pandas, NumPy, Matplotlib, and Seaborn.Exposure to deep learning frameworks like TensorFlow, Keras, or PyTorch.Good understanding of data structures and algorithms.Experience with model evaluation techniques and performance metrics.Experience with Optical Character Recognition (OCR) technologiesFamiliarity with cloud platforms and deploying models on cloud infrastructureFamiliarity with Jupyter Notebooks, version control (Git), and cloud platforms (AWS, GCP, or Azure) is a plus.Excellent written and verbal communication skills, demonstrating the ability to convey technical concepts clearlyExperience in the complete development and deployment lifecycle of an ML/AI projectCapacity to work independently and collaboratively in a remote environmentStrong analytical and problem-solving skills.Job Types: Full-time, PermanentPay: &#8377;300,000.00 - &#8377;600,000.00 per yearWork Location: Remote

Machine Learning Engineer

Sumo Logic

<div><h2 class="jobSectionHeader">Machine Learning Engineer</h2>

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data

As a Machine Learning Engineer, you'll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You'll combine machine learning, prompt engineering, and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You'll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.
<h4 class="jobSectionHeader">
Responsibilities</h4>
<ul><li>Design, implement, and optimize agentic AI components including context engineering, memory management, and prompts.</li>
<li>Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.</li>
<li>Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.</li>
<li>Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.</li>
<li>Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.</li>
<li>Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.</li>
<li>Maintain a strong bias for action&mdash;delivering incremental, well-tested improvements that directly enhance customer experience.</li>
</ul>
Required Qualifications
<ul>
<li>B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.</li>
<li>2-4 years of hands-on industry experience with demonstrable ownership and delivery.</li>
<li>Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.</li>
<li>Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.</li>
<li>Working knowledge of LLM core concepts, prompt design, and agentic design patterns.</li>
<li>Strong communication skills and a passion for shaping emerging AI paradigms.</li>
</ul>
Desired Qualifications
<ul>
<li>Prior experience building and deploying AI agents or LLM applications in production.</li>
<li>Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).</li>
<li>Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).</li>
<li>Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.</li>
</ul><h2 class="jobSectionHeader">About Us</h2>

Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.</div>

Adobe

Our Company
 
Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
 
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
 
Senior Machine Learning Engineer – Adobe Experience Platform Our Company At Adobe, you will be immersed in an exceptional work environment that is recognized around the world. Adobe is listed as Fortune’s “100 Best Companies to Work For” for 20 consecutive years. You will also be surrounded by colleagues who are committed to helping each other grow. If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer. Changing the world through digital experiences is what Adobe’s all about. We give global brands everything they need to design and deliver exceptional digital experiences. We’re passionate about redefining how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours.
 The Opportunity Adobe is redefining customer intelligence. We help enterprises understand their customers deeply—what they value, what they need—and translate that understanding into meaningful, personalized experiences. The Adobe Experience Platform (AEP) is at the heart of this mission, powering data integration, governance, advanced analytics, and intelligent services at global scale. Our next chapter focuses on agent-driven AI systems —autonomous, adaptive agents that orchestrate complex workflows, learn from data, and deliver real-time insights and actions. At the core lies our Enterprise Knowledge Base , a foundational platform that unifies structured, unstructured, and semi-structured data. This system fuels advanced AI and Generative AI applications across Adobe’s digital marketing ecosystem—empowering customers to unlock richer, more intelligent experiences. We are looking for a Senior Machine Learning Engineer who thrives on solving hard problems, scaling intelligent systems, and creating measurable impact. You’ll lead the design and development of low-latency, high-throughput services that power intelligent enterprise experiences across millions of users worldwide.
 Job Responsibilities
 Lead the technical design, implementation, and evolution of AEP Knowledge Base and Agentic AI systems.
 Design and deploy high-performance, low-latency distributed systems that scale globally.
 Work hands-on with foundation models (OpenAI, Anthropic, Llama, Gemini) and model adaptation techniques.
 Architect RAG (Retrieval-Augmented Generation) pipelines and optimize vector databases (FAISS, Pinecone, Weaviate, Milvus) for enterprise-grade AI solutions.
 Build evaluation, safety, and guardrail frameworks for responsible AI.
 Collaborate closely with research, platform, and product teams to integrate innovative AI into customer-facing solutions.
 Mentor engineers, drive technical excellence, and foster a culture of continuous learning.
 (Bonus) Contribute to or lead open-source initiatives in the LLM or agent ecosystem.
 What you will need to succeed
 6+ years of experience designing and developing large-scale, data-intensive distributed systems.
 2+ years in technical leadership roles, driving architecture and mentoring teams.
 Expertise in vector databases (Pinecone, Weaviate, Milvus) and agent frameworks (LangChain, LlamaIndex, AutoGen, Haystack Agents, Semantic Kernel).
 Hands-on experience with public cloud platforms ( Azure, AWS, or GCP ).
 Strong background in relational databases (PostgreSQL, MySQL).
 Proficiency in Java, Scala, or Python , and a deep understanding of algorithms and data structures.
 A strong sense of ownership and cost-conscious design for compute and memory efficiency.
 Excellent communication skills and the ability to collaborate effectively with multi-functional teams.
 Bachelor’s, Master’s, or PhD in Computer Science or a related technical field with equivalent experience.
 Why Adobe At Adobe, you’ll work in a culture that values creativity, collaboration, and continuous learning. Our Check-In approach fosters open feedback, career growth, and shared success. If you’re ready to shape the future of AI-powered customer experiences and make a global impact— Adobe is the place for you.
 
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
 
Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Machine Learning Engineer 4

Haystek Technologies

<div><div>We are seeking a highly skilled and motivated Machine Learning/Deep Learning Engineer with expertise in neural network development, GenAI technologies, and cloud-native deployment on AWS. 
This role will be instrumental in designing, training, and deploying advanced AI models across text, image, and audio domains, while also managing scalable cloud infrastructure and APIs.

Key Responsibilities:

Deep Learning &amp; Neural Networks
<ul>
<li>Design and implement deep learning models using TensorFlow, PyTorch, and transformer architectures.</li>
<li>Fine-tune pre-trained models for domain-specific tasks involving text, image, or audio datasets.</li>
<li>Optimize and deploy models on NVIDIA GPU hardware (e.g., A100, H100) for high-performance inference.</li>
<li>Develop LLMOps context aware pipelines for chat applications using python frameworks.</li>
<li>Collaborate with data scientists and product teams to integrate models into production systems.</li>
</ul>
API Development &amp; Integration
<ul>
<li>Develop and maintain RESTful and gRPC APIs for model serving and data access.</li>
<li>Manage the full API lifecycle, including versioning, documentation, and security.</li>
<li>Integrate APIs with internal and external applications using FastAPI or similar Python frameworks.</li>
</ul>
AWS Cloud Engineering
<ul>
<li>Create and manage AWS Container Apps, Container Registries, and Docker images.</li>
<li>Deploy and monitor AWS Web Apps for hosting AI services and dashboards.</li>
<li>Automate CI/CD pipelines using GitHub Actions for seamless deployment and updates.</li>
</ul>
Required Qualifications
<ul>
<li>2+ years of experience in Python development with a focus on deep learning.</li>
<li>Hands-on experience with transformers, Hugging Face, and custom model training.</li>
<li>Proven track record of deploying models on GPU-based infrastructure.</li>
<li>Strong understanding of API design principles and microservices architecture.</li>
<li>Experience with AWS cloud services, Docker, and GitHub Actions.</li>
<li>Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.</li>
</ul>
Preferred Qualifications
<ul>
<li>Experience with multi-modal models or generative AI applications.</li>
<li>Familiarity with MLOps tools and practices.</li>
<li>Contributions to open-source AI projects or publications in relevant fields.</li></ul></div></div>

Machine learning Engineer

Microsoft

<div>
 Are you excited by the challenge of building intelligent, autonomous systems that deliver real-world impact? The Commerce Risk Analytics team at Microsoft is looking for a machine learning engineer to design, develop, and continuously improve a multi-agent AI Risk system that enables autonomous risk transaction review and decision-making. You&rsquo;ll be working at the intersection of large language models (LLMs), applied machine learning, and platform integration&mdash;building solutions that power scenarios from fraud prevention to customer support automation.
 
 
 We&rsquo;re hiring across several focus areas, and your role will align with your expertise and interests:
 
 
 <ul>
 <li>
 Autonomous Agent Development for Risk Decision &ndash; building LLM-based decision-making agents and advancing a multi-agent risk system
 </li>
 <li>
 AI Integration &amp; MLOps &ndash; enabling scalable infrastructure, data pipelines, and operational excellence
 </li>
 <li>
 Quality &amp; Integration &ndash; focusing on agent behavior testing, UI/UX integration, and platform reliability
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 As a machine learning engineer, you will:
 
 
 <ul>
 <li>
 Design and optimize multi-agent AI architectures that enable autonomous risk assessment and decision-making at scale, leveraging agent collaboration to reduce huma manual effort and minimize false positive rates.
 </li>
 <li>
 Implement agentic ML infrastructure that automates the full model development lifecycle enabling continuous learning, adaptive optimization, and scalable risk decisioning.
 </li>
 <li>
 Build and evolve AI-driven solutions that improve the accuracy, speed, and adaptability of fraud detection across a wide range of Commerce scenarios.
 </li>
 <li>
 Develop infrastructure and MLOps pipelines to support continuous training, deployment, and monitoring
 </li>
 <li>
 Conduct rigorous behavior testing and validation, focusing on performance, safety, and real-world edge cases
 </li>
 <li>
 Integrate AI agents with Azure AI services, Microsoft Graph API, Power Platform, and internal systems
 </li>
 <li>
 Apply best practices in security, compliance, and privacy to all aspects of agent development
 </li>
 <li>
 Partner closely with product managers, engineers, and data scientists to translate complex business challenges into scalable technical solutions, ensuring alignment and impact across stakeholders
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Required Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
 </li>
 <ul>
 <li>
 OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
 </li>
 <li>
 OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
 </li>
 <li>
 OR equivalent experience.
 </li>
 </ul>
 <li>
 3+ years of experience in software engineering, data science, or machine learning
 </li>
 <li>
 2+ years experience with LLMs, prompt engineering, and the OpenAI API
 </li>
 <li>
 2+ years experience with Azure services, cloud infrastructure, and CI/CD pipelines
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience working with multi-agent frameworks such as AutoGen, Semantic Kernal and Langchain.
 </li>
 <li>
 Knowledge of MLOps practices, including containerization, infrastructure-as-code, and monitoring
 </li>
 <li>
 Exposure to Power Platform, Microsoft Graph API, or enterprise integration technologies
 </li>
 <li>
 Experience debugging skills and a solid understanding of security and data protection principles
 </li>
 <li>
 Ability to communicate technical concepts effectively with both technical and non-technical stakeholders
 </li>
 <li>
 Proficiency in Python for development and scripting
 
 
 </li>
 </ul>
 Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
 
 
 Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
 
 
 Microsoft will accept applications for the role until October 29th, 2025
 
 
 
 Other Requirements
 
 
 
 Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
 
 
 Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
</div>

Infosys

<div><h2 class="jobSectionHeader">Job Description:</h2> 
<ul>
<li>Infosys is seeking a ML Engineer with strong background in designing and deploying machine learning models using MLOPS framework for Model Management</li>
<li>Ideal candidate will work with clients to understand the issues they face diagnose problems design solutions and facilitate solution deployment on Azure ML</li>
<li>One will also have the opportunity to shape value adding consulting solutions for clients by connecting various functions of cloud components</li>
<li>Ideally the candidate uses understanding of the problem to arrive at multiple solution alternatives keeping in mind the various stakeholders and assess the pros and cons of all the alternatives to arrive at the optimal solution</li>
<li>Required Qualifications</li>
<li>Bachelor s degree or foreign equivalent required from an accredited institution</li>
<li>Will also consider three years of progressive experience in the specialty in lieu of every year of education</li>
<li>At least 7 years of experience in Information Technology</li>
<li>All applicants authorized to work in the United States are encouraged to apply</li>
<li>Candidate must live within commuting distance of Indianapolis IN or be willing to relocate</li>
<li>Travel within the US may be required</li>
<li>At least 4 years of experience in Information Technology in MLOPS</li>
<li>At least 4 years of experience Python Programming for ML Model deployment with Cleancode standards</li>
<li>At least 4 years of experience in AZURE or GCP Cloud environment</li>
<li>Azure Certified DP100 AZ AI900 or GCP equivalent including DevOps certification</li>
<li>Professional experience setting up MLOPs Framework ML CI CD pipelines Model management monitoring and Refactoring of MLOPs runs</li>
<li>At least 2 years of implementation experience in DevOps MLOps tools like Grafana Prometheus Poetry Snyk and others or equivalent in other environments</li>
<li>At least 2 years of experience in MLOPS Framework industry standards and operations KPI</li></ul> 
<h2 class="jobSectionHeader">
Key Responsibilities:</h2> 
<ul>
<li>Roles Responsibilities</li>
<li>Understand the requirements from the business and translate it into an appropriate technical requirement</li>
<li>Responsible for successful delivery of MLOps solutions and services in client consulting environments</li>
<li>Define key business problems to be solved formulate high level solution approaches and identify data to solve those problems develop analyze draw conclusions and present to client</li>
<li>Assist clients with operationalization metrics to track performance of ML Models</li>
<li>Help team with ML Pipelines from creation to execution</li>
<li>Guide team to debug on issues with pipeline failures</li>
<li>Understand and take requirements on Operationalization of ML Models from Data Scientist</li>
<li>Engage with Business Stakeholders with status update on progress of development and issue fix</li>
<li>Setup Standards related to Coding Pipelines and Documentation</li>
<li>Research on new topics services and enhancements in Cloud Technologies</li></ul> 
<h2 class="jobSectionHeader">
Technical Requirements:</h2> 
<ul>
<li>Preferred Qualifications</li>
<li>Experienced in Agile way of working manage team effort and track through JIRA</li>
<li>High Impact client communication</li>
<li>Domain experience in Retail CPG and Logistics</li>
<li>Experience in Test Driven Development and experience in using Pytest frameworks git version control Rest APIs</li>
<li>The job may entail extensive travel</li>
<li>The job may also entail sitting as well as working at a computer for extended periods of time</li>
<li>Candidates should be able to effectively communicate by telephone email and face to face</li></ul> 
<h2 class="jobSectionHeader">
Additional Responsibilities:</h2> 
<ul>
<li>EEO About Us</li>
<li>About Us</li>
<li>Infosys is a global leader in next generation digital services and consulting</li>
<li>We enable clients in more than 50 countries to navigate their digital transformation</li>
<li>With over four decades of experience in managing the systems and workings of global enterprises we expertly steer our clients through their digital journey</li>
<li>We do it by enabling the enterprise with an AI powered core that helps prioritize the execution of change</li>
<li>We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight</li>
<li>Our always on learning agenda drives their continuous improvement through building and transferring digital skills expertise and ideas from our innovation ecosystem</li>
<li>Infosys provides equal employment opportunities to applicants and employees without regard to race color sex gender identity sexual orientation religious practices and observances national origin pregnancy childbirth or related medical conditions status as a protected veteran or spouse family member of a protected veteran or disability</li></ul> 
<h2 class="jobSectionHeader">
Preferred Skills:</h2>
Technology-&gt;Machine learning-&gt;data science</div>

Code Graphers

Key ResponsibilitiesModel Development &amp; Implementation<ul><li>Design, train, and fine-tune machine learning and deep learning models for NLP, computer vision, and predictive analytics tasks.</li><li>Work with frameworks like TensorFlow, PyTorch, and Scikit-learn for building and deploying ML models.</li><li>Assist in developing RAG (Retrieval Augmented Generation) pipelines and LLM-based applications under senior supervision.</li><li>Implement and maintain APIs using frameworks like FastAPI, Flask, or Django for ML model integration.</li></ul>Data Handling &amp; Preprocessing<ul><li>Perform data cleaning, feature extraction, and transformation for model readiness.</li><li>Contribute to building and maintaining data pipelines for training and inference stages.</li></ul>Deployment &amp; MLOps<ul><li>Containerize ML solutions using Docker and participate in deploying models to production environments.</li><li>Support MLOps workflows, version control using DVC, and CI/CD pipelines for continuous delivery.</li></ul>Research &amp; Collaboration<ul><li>Stay updated with the latest trends in AI, LLMs, and computer vision.</li><li>Collaborate with cross-functional teams, data engineers, and senior ML engineers to ensure robust system integration.</li><li>Document workflows, experiments, and technical findings clearly.</li></ul>QualificationsEducation:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.</li></ul>Experience:<ul><li>2&ndash;3 years of hands-on experience in machine learning model development and deployment.</li><li>Strong understanding of fundamental ML algorithms and their mathematical background.</li><li>Exposure to NLP, Computer Vision, or LLM-based systems is preferred.</li></ul>Technical Skills:<ul><li>Proficient in Python and familiar with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.</li><li>Knowledge of LLMs, LangChain, or RAG frameworks is a plus.</li><li>Experience with RESTful APIs and backend integration.</li><li>Familiarity with Git, Docker, and cloud platforms (AWS, GCP, or Azure).</li></ul>Nice to Have<ul><li>Experience with LoRA, QLoRA, or model fine-tuning techniques.</li><li>Familiarity with image classification, object detection, or segmentation tasks.</li><li>Exposure to auto-scaling, model optimization, or embedded ML applications.</li><li>Interest in learning advanced AI concepts like multi-agent systems, meta-learning, and generative AI.</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Did you have experience with Computer vision, LLM, nlp and Audio?</li></ul>Experience:<ul><li>Machine Learning : 2 years (Required)</li></ul>Work Location: In person

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