Remote senior ML engineer jobs

We, at Turing, are looking for talented remote senior ML engineers who will join the AI team and collaborate with data scientists and software engineers to develop and implement production-ready AI applications. Get an excellent opportunity to collaborate closely with the best minds while working at top U.S. firms.

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Job description

Job responsibilities

  • Analyze user behavior, participate in project ideation and translate analytical use cases into technical end-to-end solutions
  • Design and implement large-scale machine learning algorithms, data pipelines, and back-end services
  • Design and train models to develop efficient machine learning applications
  • Keep abreast with the latest developments in AI-ML and NLP spaces
  • Participate in all stages of development process and take ownership of complex projects
  • Define metrics and run A/B tests to measure the workflow impact
  • Guide and mentor the junior ML engineers
  • Explain technical and complex concepts to non-technical users

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science, Statistics (or equivalent experience)
  • At least 5+ years of experience in applied machine learning (rare exceptions for highly skilled developers)
  • Prior experience with natural language processing and machine learning algorithms
  • Profound knowledge in programming languages including Python, Java, R, PHP, Scala, etc.
  • Experience with deep learning frameworks like TensorFlow, Pytorch and libraries like scikit-learn
  • Expertise in data processing frameworks like Apache Spark, Flink, etc.
  • Understanding of data structures, neural networks, data modeling and software architecture
  • Fluency in English language for effective communication
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Experience in developing and training ML models
  • Experience with graph learning, MATLAB, SQL, and AWS technologies
  • Hands-on experience in Git, Github and CI/CD principles
  • Ability to design, develop, and maintain recommendation services
  • Great analytical and problem-solving skills
  • Ability to work independently and take up ownership
  • Strong communication and leadership skills

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How to become a senior machine learning engineer ?

Machine learning has been a part of the space for the last 10-20 years. But the recognition it has received is overwhelming. As the industry is growing at a tremendous rate, it has become one of the hottest jobs. It is expected to grow even more in the coming years. So the future of machine learning is shining bright.

Since it's not an entry-level job. An expert engineer must have relevant expertise in both fields- data science and software engineering. This profile is an amalgamation of degree, knowledge and experience. Therefore, machine learning engineers are always in demand. The industries where an individual can seek a career are – IT, marketing, finance and businesses.

What is the scope of a senior machine learning engineer?

Machine learning is a process where machines learn and improve on their own. The system enhances itself on its own with minimum/ no human interference. They keep on improving themselves based on the previous data and its analysis. Engineers prepare algorithms that are used by the machines for improvement and action.

Machine learning opens lucrative career options for the novice and professionals. Top companies like Apple, Google, Amazon, and many more hire ML engineers to achieve various business goals. An experienced machine learning takes care of designing and implementing machine learning algorithms. A fresher can start their career as an ML engineer, analyst or data scientist. However, a professional can make a career in the following fields:

  • Sr. Machine Learning Engineer:
  • Senior Data Scientist
  • Sr. Data Architect

What are the roles and responsibilities of a senior machine learning engineer?

The roles and responsibilities of an sr. machine-learning engineers are almost the same in every company. Although, some of the responsibilities depend on the project, company and goals. Here, we have listed some of the common roles and responsibilities that are the same for every sr. machine learning engineer.

  • Should know how to implement machine learning algorithms and other methodologies.
  • Help junior ml engineers to work effectively
  • Perform machine learning tests and experiments
  • Collaborate with data scientists and bring solutions to existing problems.
  • Review and ensure the quality of programme code
  • Must remain up-to-date with latest ml trends and technologies
  • Must be ready to lead machine learning projects
  • Help in the process of developing machine learning applications

How to become a senior machine learning engineer?

To become an sr. machine engineer, you should have good knowledge of data science, programming languages and mathematics. For someone who is aspiring to become a machine learning engineer, It is good to have an undergraduate degree in computer science or a relevant degree. They should have sound technical skills to comprehend data and should have worked for more than 5 years to become senior machine learning developers.

Sr. Machine learning engineers should keep themselves updated with the latest trends, new algorithms. You can also attend courses workshops on machine learning and data science. Knowledge and hands-on experience on various projects are also required for an sr. ml engineer. As this will help you get your ideal job.

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Skills required to become a senior machine learning engineer

To get a job as a senior ml engineer, you must have relevant years of experience as a machine learning engineer. Along with the experience, there are certain skills that every sr. ml engineer must possess:

1. Knowledge of programming languages

An understanding and working knowledge of programming languages is a must for an sr. machine-learning engineer. Knowledge of languages like Python, Java, SQL, Scala and PHP. As the knowledge of languages is important for application development, the engineer must also be proficient in mathematics, statistics and data science.

2. Software Engineering

As an ML engineer, you have to deliver software. You must understand how everything works together to generate the desired output. They must also be ready to overcome any roadblocks while increasing productivity.

They should have a keen understanding of the functionality and working knowledge of REST APIs, libraries and queries. Also, an sr. ml engineers should have hands-on experience in system design, version control, documentation, etc.

3. Machine Learning Algorithms

You should have a decent understanding of machine learning algorithms available through APIs, libraries and packages. You should also know the pros and cons of different approaches (underfitting, data leakage, etc). Online communities like Kaggle also help machine learning engineers in keeping themselves updated with trends, solving problems and reaching solutions.

4. Data Modeling

Data modeling is a process of creating data models by applying different techniques. The data models are stored in databases. It helps in analyzing data that is required for business functions. One of the most important parts of the job is to evaluate how good the data model is based on different conditions like accuracy or error.

5. Problem-solving Skills

As problems are a part of their jobs, ML engineers should have great problem-solving skills. This will help them in solving problems and help them make better decisions. As an sr ml engineer, you will be responsible for mentoring junior ml engineers by solving any roadblock faced by them.

Interested in remote machine learning engineer jobs?

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How to get a remote senior machine learning engineer job?

To grow your career as an sr. machine learning engineer, you must have good years of experience as an ML engineer. Along with the experience, you should also keep yourself updated with the latest developments in the machine learning and data science space.
At Turing, we help developers get remote jobs that are in line with their goals. Turing helps you grow your career professionally with top Silicon Valley companies. You can join the network of developers worldwide and accelerate your career with Turing.

Why become a senior machine learning engineer at Turing?

Elite U.S jobs

Long-term opportunities to work for amazing, mission-driven U.S. companies with great compensation.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you'll never have to apply for other remote CMS developer jobs

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top U.S. firms from the comfort of your home.

Great compensation

Working with top U.S. corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their senior machine learning engineer?

At Turing, we help each developer get matched with silicon valley companies and get their desired job. However, Turing does suggest a number they think is right for the developer. The salary depends on your experience, clients’ needs and market conditions.

Frequently Asked Questions

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Currently, we have openings only for the developers because of the volume of job demands from our clients. But in the future, we might expand to other roles too. Do check out our careers page periodically to see if we could offer a position that suits your skills and experience.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

No, the service is absolutely free for software developers who sign up.

Ideally, a remote developer needs to have at least 3 years of relevant experience to get hired by Turing, but at the same time, we don't say no to exceptional developers. Take our test to find out if we could offer something exciting for you.

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In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

Explore remote developer jobs

briefcase
Solutions Engineer

About the role

We are looking for Solution Engineers to partner directly with customers and lead the end-to-end delivery of high-impact technical solutions. Successful candidates will need to be able to work with customer teams, translating real-world challenges into production-ready systems that leverage Generative AI, Computer Vision, and Machine Learning. This role is a blend of software engineering, ML engineering, architecture, and consulting. Engineers will design and deploy solutions, integrate models, build custom workflows, and guide customers through successful implementation.

Qualifications

  • 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.
  • German language proficiency (C1 or native)
  • Strong proficiency in Python, JavaScript/TypeScript, Go, or similar production-oriented languages.
  • Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.
  • Direct experience with Generative AI (LLMs, multimodal models, vector databased, or RAG) and applying them to real-world problems.
  • Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).
  • Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).
  • Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Excellent communication skills with both technical and non-technical audiences.
  • Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.
  • Willingness and ability to travel frequently.
  • Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.
  • Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).
  • Experience building APIs, microservices, or distributed systems.
  • Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML).
  • Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).
  • Experience in startup or high-growth environments.

Key Responsibilities

  • Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements.
  • Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.
  • Lead full project lifecycles: scoping, solution design, development, implementation, testing, deployment, and iteration.
  • Integrate and optimize AI/ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.
  • Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
  • Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.
  • Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.
  • Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.
  • Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.
  • Mentor junior engineers and contribute to internal best practices for FDE delivery.

Offer Details

  • Full-time contractor (no benefits)
  • Remote only, full-time dedication (40 hours/week)
  • Same overlap with PST required, work mostly done in EU timezones
  • Competitive compensation package.
  • Opportunities for professional growth and career development.
  • Dynamic and inclusive work environment focused on innovation and teamwork
Software
11-50 employees
Refinement of ModelsMachine LearningData Science+ 10
briefcase
Solutions Engineer

About the role

We are looking for Solution Engineers to partner directly with customers and lead the end-to-end delivery of high-impact technical solutions. Successful candidates will need to be able to work with customer teams, translating real-world challenges into production-ready systems that leverage Generative AI, Computer Vision, and Machine Learning. This role is a blend of software engineering, ML engineering, architecture, and consulting. Engineers will design and deploy solutions, integrate models, build custom workflows, and guide customers through successful implementation.

Qualifications

  • 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.
  • Strong proficiency in Python, JavaScript/TypeScript, Go, or similar production-oriented languages.
  • Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.
  • Direct experience with Generative AI (LLMs, multimodal models, vector databased, or RAG) and applying them to real-world problems.
  • Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).
  • Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).
  • Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Excellent communication skills with both technical and non-technical audiences.
  • Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.
  • Willingness and ability to travel frequently.
  • Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.
  • Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).
  • Experience building APIs, microservices, or distributed systems.
  • Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML).
  • Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).
  • Experience in startup or high-growth environments.

Key Responsibilities

  • Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements.
  • Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.
  • Lead full project lifecycles: scoping, solution design, development, implementation, testing, deployment, and iteration.
  • Integrate and optimize AI/ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.
  • Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
  • Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.
  • Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.
  • Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.
  • Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.
  • Mentor junior engineers and contribute to internal best practices for FDE delivery.

Offer Details

  • Full-time contractor (no benefits)
  • Remote only, full-time dedication (40 hours/week)
  • Overlap with EST or PST timezones
  • Competitive compensation package.
  • Opportunities for professional growth and career development.
  • Dynamic and inclusive work environment focused on innovation and teamwork
Software
11-50 employees
Refinement of ModelsMachine LearningData Science+ 10
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