machine learning engineer

Bazzle Balloons

What You'll Work OnAs a Junior Machine Learning Engineer, you will:<ul><li>Assist in the design, development, and deployment of machine learning models and pipelines.</li><li>Support the automation of training, evaluation, and deployment workflows.</li><li>Contribute to the implementation of MLOps best practices including versioning, monitoring, and model management.</li><li>Work with tools like Docker, MLflow, Weights &amp; Biases, or similar for reproducible experimentation.</li><li>Collaborate with data scientists, backend engineers, and product teams to deliver production-ready ML solutions.</li><li>Learn to deploy models in cloud environments such as AWS, GCP, or Azure.</li><li>Stay up to date with machine learning advancements and apply relevant techniques to improve performance and scalability.</li></ul>Core Skills &amp; QualificationsWe are looking for someone with:<ul><li>1+ years of experience in machine learning or data science roles.</li><li>Proficient in Python and popular ML libraries like Scikit-learn, Pandas, TensorFlow, or PyTorch.</li><li>Solid understanding of ML concepts such as supervised/unsupervised learning, feature engineering, and evaluation metrics.</li><li>Basic experience working with SQL or NoSQL databases.</li><li>Strong understanding of data structures and algorithms.</li><li>Familiarity with API integration and deploying ML models in production environments is a plus.</li><li>Exposure to cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes) is a plus.</li><li>Experience with tools like MLflow, LangChain, LangSmith, or vector databases is a bonus.</li><li>Good communication skills, a growth mindset, and an eagerness to learn.</li></ul>Nice-to-Have<ul><li>Experience with building and maintaining Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases and retrieval techniques to enhance LLM-powered applications.</li><li>Familiarity with distributed computing and big data technologies.</li><li>Contributions to open-source ML projects or research publications.</li></ul>Job Type: Full-timeEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>machine learning or data science roles: 2 years (Required)</li><li>Python: 1 year (Required)</li><li>ML libraries like Scikit-learn, Pandas, TensorFlow, PyTorch.: 1 year (Required)</li><li>SQL or NoSQL databases: 1 year (Required)</li><li>data structures and algorithms: 1 year (Required)</li><li>API integration and deploying ML models: 1 year (Required)</li><li>cloud platforms (AWS, GCP, or Azure) : 1 year (Required)</li><li>containerization tools (Docker, Kubernetes): 1 year (Preferred)</li><li>MLflow, LangChain, LangSmith: 1 year (Preferred)</li><li>vector databases: 1 year (Preferred)</li></ul>Work Location: Remote

Machine Learning Engineer

What You'll Work OnAs a Junior Machine Learning Engineer, you will:<ul><li>Assist in the design, development, and deployment of machine learning models and pipelines.</li><li>Support the automation of training, evaluation, and deployment workflows.</li><li>Contribute to the implementation of MLOps best practices including versioning, monitoring, and model management.</li><li>Work with tools like Docker, MLflow, Weights &amp; Biases, or similar for reproducible experimentation.</li><li>Collaborate with data scientists, backend engineers, and product teams to deliver production-ready ML solutions.</li><li>Learn to deploy models in cloud environments such as AWS, GCP, or Azure.</li><li>Stay up to date with machine learning advancements and apply relevant techniques to improve performance and scalability.</li></ul>Core Skills &amp; QualificationsWe are looking for someone with:<ul><li>1+ years of experience in machine learning or data science roles.</li><li>Proficient in Python and popular ML libraries like Scikit-learn, Pandas, TensorFlow, or PyTorch.</li><li>Solid understanding of ML concepts such as supervised/unsupervised learning, feature engineering, and evaluation metrics.</li><li>Basic experience working with SQL or NoSQL databases.</li><li>Strong understanding of data structures and algorithms.</li><li>Familiarity with API integration and deploying ML models in production environments is a plus.</li><li>Exposure to cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes) is a plus.</li><li>Experience with tools like MLflow, LangChain, LangSmith, or vector databases is a bonus.</li><li>Good communication skills, a growth mindset, and an eagerness to learn.</li></ul>Job Type: Full-timeWork Location: Remote

Jr. Machine Learning Engineer

Apple

<div>Are you passionate about applying cutting-edge machine learning techniques to solve real- world problems in natural language processing, computer vision, recommendation systems, knowledge graph and more? Join the ACD Labs at Apple, where we're developing innovative AI solutions to power the next generation of digital experiences. We're seeking an exceptional Applied Machine Learning Engineer to join our research team, focusing on practical applications of advanced ML techniques. In this role, you'll work on challenging problems in NLP, deep neural networks, recommendation systems, and computer vision, translating state-of-the-art research into real-world solutions that enhance our products and services. As an Applied Machine Learning Engineer, you'll collaborate closely with our research scientists and distributed systems engineers, big data engineers and system architects to implement and fine-tune models for production environments. You'll have the opportunity to work on projects that directly impact millions of users, while staying at the forefront of AI innovation.
 
 
Description 
 
Implement and fine-tune state-of-the-art machine learning models for NLP, computer vision, recommendation systems and other deep neural networks. Develop end-to-end ML pipelines, from data preprocessing to model deployment with focus on MLOps. Collaborate with research scientists to translate theoretical concepts into practical applications Optimize model performance for production environments, considering scalability and efficiency Conduct experiments to evaluate and improve model accuracy and effectiveness Implement and adapt latest advancements in deep learning architectures for specific use cases Contribute to the development of ML-powered features for Apple's digital products and services Work closely with cross-functional teams to integrate ML solutions into existing systems Stay current with the latest d
 
 
Minimum Qualifications 
<ul><li>
Bachelor's or Master's degree in Computer Science, Machine Learning, or a related
</li><li>technical field
</li><li>3-5 years of experience in applied machine learning, with a focus on NLP, computer vision,
</li><li>or recommendation systems
</li><li>Strong programming skills in Python and experience with ML frameworks such as PyTorch
</li><li>or TensorFlow
</li><li>Proven track record of implementing and fine-tuning deep learning models for real-world
</li><li>applications
</li><li>Experience with natural language processing techniques, including transformers and
</li><li>language models
</li><li>Familiarity with computer vision algorithms and deep learning architectures for image and
</li><li>video processing
</li><li>Knowledge of recommendation system algorithms and their practical applications
</li><li>Strong problem-solving skills and ability to translate complex problems into effective ML
</li><li>solutions
</li><li>Excellent communication skills and ability to work in a collaborative research environment
</li></ul> 
Preferred Qualifications 
<ul><li>
Experience with deploying ML models in production environments
</li><li>Familiarity with cloud-based ML platforms and services
</li><li>Knowledge of MLOps practices and tools
</li><li>Experience with multimodal learning and fusion of different data types
</li>Contributions to open-source ML projects or publications in applied ML 
<li>
</li></ul> 
 
Submit CV</div>

Applied Machine Learning Engineer

Infostack Tech

Job Title: Machine Learning EngineerAbout the Role:Infostack is hiring a skilled Machine Learning Engineer with 2+ years of experience in creating and deploying machine learning models. The role involves leveraging cutting-edge ML algorithms to solve complex business problems.Responsibilities:- Build, train, and deploy ML models using frameworks like TensorFlow, PyTorch, and Scikit-learn.- Develop and maintain scalable ETL pipelines for data preprocessing and transformation.- Optimize machine learning workflows for large-scale data processing.- Collaborate with teams to integrate ML capabilities into cloud-based services.- Monitor and improve model performance in production environments.Requirements:- Expertise in Python and machine learning frameworks.- Strong understanding of ML and deep learning algorithms.- Experience with ETL pipelines and data engineering tools like Apache Spark.- Proficiency with MLOps tools such as MLflow or DVC.- Familiarity with cloud platforms (AWS, GCP, Azure).- Strong English Communication skills.Nice to have:- Knowledge of containerization tools like Docker and orchestration with Kubernetes.- Experience working with structured and unstructured datasets.Job Timing:05:00 PM to 02:00 AM (Remote)Job Type: Full-timeWork Location: Remote

<div>Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something - you&rsquo;ll add something. Siri is fundamental to how users experience Apple products and services. Our team develops foundational ML systems that power Siri's evolution, translating cutting-edge AI research into seamless user experiences across the Apple ecosystem. We value passion for excellence and a deep commitment to excellence, and if you want to impact millions of customers by working on the most advanced technology solutions, we want to talk to you. 
 
Description 
 
The Siri System SW group at Apple is actively looking for a highly motivated Machine Learning Engineer to contribute to and build the next generation of Siri. The successful candidate will demonstrate deep knowledge of, and hands-on experience, with designing, implementing, and optimizing machine learning algorithms to tackle ambitious problems. Candidate is expected to be proficient in machine learning and deep learning and be comfortable in applying their machine learning background and problem-solving skills to develop high-quality machine learning solutions that contribute to Apple's revolutionary roadmap. As a Machine Learning Engineer in the Siri System SW team at Apple, you will partner with algorithm designers to collaboratively design machine learning based solutions to solve high-impact problems on Apple product(s). The primary responsibilities associated with this role, include algorithm design, implementation and optimization, integrating ground breaking research into production frameworks, and collaborating closely with product teams before and after feature launch. 
 
Responsibilities 
<ul><li>
You will work multi-functionally with multiple teams at Apple, drive requirements and deliver the end solution</li><li>
You will help evaluate various candidate approaches for optimizing machine learning pipelines for training and inference - these could include (but are not limited to) algorithm tuning, hyper parameter tuning, hardware and software co-design.</li><li>
You will write clean, maintainable and production code with appropriate documentation and tests.</li><li>
You will debug quality related issues in machine learning pipelines.</li><li>
You will contribute to architecture decisions, design reviews and peer code reviews.</li><li>
You will be a force-multiplier, by enabling team-members to be more productive</li></ul> 

Minimum Qualifications 
<ul><li>
Strong programming skills in Python and/or C++ with demonstrated ability in using these languages for machine learning (machine learning) modeling and applied research</li><li>
Hands-on experience developing end to end machine learning systems</li><li>
Strong problem solving skills and passionate about delivering high-quality products, seeking to solve everyday problems in innovative ways</li><li>
Ability to work under tight schedules and deliver under pressure</li><li>
Ability to thrive in a collaborative environment and communicate clearly and confidently with partner teams</li><li>
Masters or PhD in Computer Science, Machine Learning Engineering or equivalent professional experience</li></ul> 

Preferred Qualifications 
<ul><li>
Hands-on experience working (training, fine-tuning, optimizing, deploying) with large language models and natural language understanding</li><li>
Expertise in using machine learning toolkits such as PyTorch, Hugging Face etc.</li></ul> 

Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $126,800 and $220,900, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 
 
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 . 
 
Submit Resume</div>

Machine Learning Engineer, Siri

Siemens Energy

<div><h2 class="jobSectionHeader">A Snapshot of Your Day</h2>
We are seeking a skilled AI/Machine Learning Engineer to join our team and help build innovative machine learning solutions that drive business outcomes. You will collaborate with multi-functional teams including data scientists, software engineers, and product managers to design, develop, and maintain robust machine learning models and workflows. Your work will involve transforming raw data into actionable insights, optimizing algorithms for performance, and integrating AI capabilities into dynamic applications to provide seamless user experiences and enhanced functionality !<h2 class="jobSectionHeader">
How You&rsquo;ll Make an Impact</h2><ul>
<li>Create end-to-end workflows for the training and inference pipeline of the machine learning models.</li>
<li>Responsible for designing, developing, and implementing multi-step RAG (Retrieval-Augmented Generation), agentic, or tool-augmented workflows using Python and frameworks like LangChain and LangGraph.</li>
<li>Know the latest advancements in agentic AI, large language model (LLM) orchestration, and tools within the Python ecosystem.</li>
<li>Build and optimize RAG pipelines using vector stores such as FAISS, AWS OpenSearch.</li>
<li>Implement solutions for processing and analyzing time series data using libraries like Pandas and NumPy, enhancing data-driven decision-making.</li>
<li>Write, evaluate, and optimize prompts for LLMs to improve the accuracy and efficiency of AI-driven applications.</li>
<li>Collaborate with other developers to create, deploy, and maintain applications for different platforms.</li>
<li>Write and review code for multiple applications, ensuring high quality and readability.</li>
<li>Conduct unit testing and integration analysis to refine product performance.</li>
<li>Ensure consistency between delivered product features and business requirements.</li>
<li>Optimize application performance and resolve issues across different platforms.</li>
</ul><h2 class="jobSectionHeader">What You Bring</h2><ul>
<li>You hold a Bachelor&rsquo;s degree in Computer Science, Information Technology, Software Engineering, or a related field.</li>
<li>Proven 3+ years of experience as a Machine Learning Engineer or AI Developer in building complex AI-driven applications.</li>
<li>Proficient programming experience in Python, with hands-on knowledge of libraries such as scikit-learn, Numpy, Pandas, Langchain, LangGraph, TensorFlow, or PyTorch.</li>
<li>Familiarity with building APIs (Application Programming Interfaces) and integrating third-party libraries.</li>
<li>Understanding of AWS services for deploying FastAPI applications (e.g., Lambda, S3, ECS, SageMaker, StepFunctions) or Basic understanding of the Azure services.</li>
<li>Familiarity with the Agile development lifecycle.</li>
<li>Knowledge of version control tools such as Git and CI/CD processes using Jenkins or similar tools.</li>
<li>Strong problem-solving and critical-thinking abilities.</li>
<li>Strong communication skills to support engagement with various collaborators.</li>
<li>Ability to work under pressure and adhere to tight deadlines.</li>
<li>Capability to switch between different projects as needed (e.g., application development vs. AI/ML Research).</li>
<li>Experience with backend integrations relevant to machine learning applications and data pipelines, such as AWS services (e.g., SageMaker, Lambda, S3, Step Function) or other cloud-based platforms (Azure).</li>
<li>Understanding of standard methodologies for deploying and managing AI/ML models in production environments.</li>
<li>Understanding of time series analysis techniques and familiarity with handling time-dependent data using libraries such as Sklearn, Pandas and NumPy, along with knowledge of leveraging LLMs for various natural language processing tasks and user interactions in AI applications.</li>
<li>Prior experience with model testing and validation frameworks (e.g., MLflow, Pytest for Python) to ensure the robustness and reliability of machine learning solutions.</li>
<li>Proficiency in data engineering practices, including data wrangling, cleaning, and preprocessing for machine learning tasks.</li>
</ul><h2 class="jobSectionHeader">About the Team</h2>
In the central Digital Products and Solutions (DPS) organization, our Software Application and Engineering department is responsible for developing software solutions for both internal and external customers.
In DPS, our software products already cover a wide range of categories, and we see many opportunities for growth: Asset Performance Management, Energy Management, Asset Monitoring, Asset Health Prediction, Customer Portal &amp; AI-assisted Applications, Connectivity &amp; Edge, Backend Core / Domain / Platform Services, and Professional Services.
Who is Siemens Energy?
At Siemens Energy, we are more than just an energy technology company. We meet the growing energy demand across 90+ countries while ensuring our climate is protected. With ~100,000 dedicated employees, we not only generate electricity for over 16% of the global community, but we&rsquo;re also using our technology to help protect people and the environment.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
Find out how you can make a difference at Siemens Energy:
<h2 class="jobSectionHeader">https://www.siemens-energy.com/employeevideo</h2>
Our Commitment to Diversity
Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character &ndash; no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.<h2 class="jobSectionHeader">
Rewards/Benefits</h2><ul>
<li>Employees are eligible for Remote Working arrangements up to 2 days per week.</li>
<li>Opportunities to work with a distributed team</li>
<li>Opportunities to work on and lead a variety of innovative projects</li>
<li>Medical benefits</li>
<li>Time off/Paid holidays and parental leave</li>
<li>Continual learning through the Learn@Siemens-Energy platform</li>
</ul><h2 class="jobSectionHeader">https://jobs.siemens-energy.com/jobs</h2></div>

AI/Machine Learning Engineer

Vodafone

<div>
 
 Join Us
 
 
 
 At Vodafone, we&rsquo;re not just shaping the future of connectivity for our customers &ndash; we&rsquo;re shaping the future for everyone who joins our team. When you work with us, you&rsquo;re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.
 
 
 
 Role Purpose:
 
 
 
 The Junior ML Engineer is a core member of the agile teams facilitating trained ML models to deliver E2E solutions as a final product that fulfill the COE automation target. The junior machine Learning Engineer job is to mainly develop and design machine learning pipeline / integrations using different machine learning platforms and his software engineering / cloud skills.
 
 
 
 Key accountabilities and decision ownership:
 
 
 
 <ul>
 <li>
 Develop solutions for real world, large scale problems
 </li>
 <li>
 Design, develop, test, deploy, maintain and improve software
 </li>
 <li>
 Manage individual project priorities, deadlines and deliverables
 </li>
 <li>
 Create and maintain ML pipeline and workflows
 
 
 
 </li>
 </ul>
 Develop and deploy integrations/APIs on cloud.
 
 
 
 Core competencies, knowledge and experience:
 
 
 
 <ul>
 <li>
 Bachelor Degree in computer science and/or engineering or equivalent with 0-3 years of relevant experience
 </li>
 <li>
 Working in international, distributed teams
 </li>
 <li>
 Experience of working on projects that span multi-disciplinary areas of differing size and complexity to meet business expectations and deliver results
 </li>
 <li>
 Confident and able to liaise and influence at all levels within Vodafone and/or relevant customer organizations
 
 
 
 </li>
 </ul>
 Able to communicate effectively across organizational, technical and political boundaries, understanding the context
 
 
 
 Must have technical / professional qualifications:
 
 
 
 <ul>
 <li>
 Computer Science fundamentals in object-oriented design, data structures, algorithms and complexity analysis
 </li>
 <li>
 Proficiency in Python
 </li>
 <li>
 Information Retrieval
 </li>
 <li>
 Data Mining
 </li>
 <li>
 Natural language Programming
 </li>
 <li>
 Machine Learning
 </li>
 <li>
 Python Data Science stack (NLTK, Pandas, Numpy)
 </li>
 <li>
 Proficiency in HTML, Javascript, CSS and general Web 2.0 techniques
 </li>
 <li>
 Experience taking a leading role in building complex software systems that have been successfully delivered to customers
 </li>
 <li>
 Knowledge of professional software engineering practices &amp; best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
 </li>
 <li>
 Experience with GCP and/or AWS products
 </li>
 <li>
 Hands-on Experience with Sklearn, Tensor Flow
 </li>
 <li>
 Experience with Django/ Flask
 </li>
 <li>
 Familiarity with react js
 </li>
 <li>
 RESTful API
 </li>
 <li>
 Familiarity with docker and kubernetes
 
 
 
 </li>
 </ul>
 #VOIS #BeUnrivalled #Createthefuture
</div>

Machine Learning Engineer (VOIS)

Search 10000+ Machine learning engineer jobs near you this September. New roles added regularly across leading industries. Apply today.

10000 machine learning engineer jobs NEAR_ME

Machine Learning Engineer

Jr. Machine Learning Engineer

Applied Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer, Siri

AI/Machine Learning Engineer

Machine Learning Engineer (VOIS)