Remote machine learning scientist jobs

We, at Turing, are looking for talented machine learning scientists who can help solve a range of exciting problems. We offer the best ML jobs that provide candidates a unique opportunity to make an impact by applying advanced machine learning concepts to our products.

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Job description

Job responsibilities

  • Enhance our existing machine learning systems using your core coding skills and ML knowledge
  • Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems
  • Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics
  • Design features and builds large scale recommendation systems to improve targeting and engagement
  • Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers

Minimum requirements

  • BS, MS, or Ph.D. in computer science or a relevant technical field (AI/ML preferred)
  • Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
  • Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance, and Data mining, understanding of NLP approaches like W2V or Bert
  • 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing
  • Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them
  • Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (sci-kit-learn, XGBoost, Keras/Tensorflow) tools
  • Good understanding of mathematical foundations of machine learning algorithms
  • Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST)

Preferred skills

  • First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals
  • Strong performance in Kaggle competitions
  • 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
  • Strong communication skills
  • Experienced in leading large-scale multi-engineering projects
  • Flexible and a positive team player with outstanding interpersonal skill

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How to become an ML scientist ?

Machine learning is a branch of artificial intelligence that allows a system to learn from data rather than explicit programming. Before an ML software is used in its intended application, it must first be "trained." The programming uses algorithms that consume training data provided by an ML scientist, allowing for more precise models to be created using that data. Thus, a machine learning model is a result of using data ingestion to train an ML algorithm. When an ML model is fed real-world data after it has been trained, it produces an output. Hence, it becomes a necessity for IT and other companies to post remote ML scientist jobs.

Supervised learning, unsupervised learning, reinforcement learning, and deep learning are the four major methodologies used by an ML scientist. An ML scientist needs to have an extensive mathematical understanding to recognize diverse sets of data and describe the fundamental patterns and tendencies in the data. When looking for ML scientist jobs, you must be able to use advanced programming techniques and algorithms to build a system that can ingest a specific type of input and transform it into the appropriate modeling output.

What is the scope of ML development?

Machine learning is gaining traction in a variety of industries, including banking and finance, information technology, media and entertainment, gaming, and the automobile industry. Because the breadth of ML is so broad, there are several areas where academics are trying to revolutionize the world in the future.

When it comes to work prospects, the scope of ML in the world is vast in contrast to other career disciplines. According to Gartner, the field of artificial intelligence and machine learning will employ 2.3 million people by 2022. A remote ML scientist jobs compensation is also significantly greater than that of other job categories.

According to Forbes, an ML scientist in the United States earns an average of US$99,007. In terms of compensation and work chances, the machine learning field has a lot to offer. It is a viable choice to pursue a lucrative career in machine learning by getting ML scientist jobs.

What are the roles and responsibilities of an ML scientist?

On the team, the ML scientists’ responsibilities include a variety of tasks, such as -

  • Prototypes in data science should be studied and converted.
  • Machine learning systems and schemes must be designed and developed.
  • Using test findings, undertake statistical analysis and fine-tune models.
  • To locate available datasets for training purposes on the internet.
  • To train and retrain ML systems and models as needed.
  • Extend and improve existing ML frameworks and libraries.
  • To create ML apps that meet the needs of customers and clients.
  • To investigate, test, and deploy appropriate ML algorithms and tools.
  • To assess ML algorithms’ problem-solving skills and applications and rate them according to their likelihood of success.
  • To better understand and discover discrepancies in data distribution that could affect model performance when deployed in real-world scenarios by exploring and visualizing data.

Aside from these, for remote ML scientist jobs, roles and responsibilities may include other related tasks. The industry is still in its early stages and many things remain unknown, each organization has its unique set of productive automation approaches.

How to become an ML scientist?

Before deciding whether to pursue a bachelor's or master's degree or enroll in an online Bootcamp, you should have a clear idea of what you want to get out of a career in machine learning. Some remote ML scientist jobs will demand a bachelor's degree in computer science, mathematics, statistics, or a related discipline, while others will require a master's or doctoral degree. Others will evaluate your qualifications based on your work experience and skill transferability.

ML scientists have a lot in common with data scientists, which is one of the things that sets them apart from traditional software scientists. Anyone interested in ML scientist jobs should know how to collect, clean, optimize, and query data sets, as well as grasp data models and connect data science findings with software scientists building blocks.

Let's take a look at the knowledge and skills you'll need to join the ranks of remote ML scientists.

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Skills required to become an ML scientist

The sector of ML scientist jobs is a young and quickly evolving one. As a result, becoming an ML scientist does not require a one-size-fits-all skillset. There are a multitude of ways to break into the sector depending on your educational background, technical skills, and areas of interest. AI and machine learning are already reshaping IT, FinTech, Healthcare, Education, Transportation, and other industries, and there is still a long way to go. Organizations are focused on the value of AI, pushing past the trial stage and focusing on ML adoption. As a result, shortly, remote ML scientist jobs will be in more demand.

The seven abilities you must acquire if you want to advance your career with exceptional US employment are:

1. Programming languages

The ability to deal with a range of programming languages is the first skill that ML scientists must possess. According to GitHub, the top 10 machine learning languages are Python, C++, JavaScript, Java, C#, Julia, Shell, R, TypeScript, and Scala. While Python is the most popular programming language, Scala is gaining popularity in specific areas, such as interacting with big data frameworks like Apache Spark.

2. Data developing (ETL)

The pre-processing and storage of raw data generated by ML systems is one of the most crucial steps in their development. When new data is generated, the ML scientist must create ETL (Extract, Transform, Load) pipelines to process, cleanse, and store it so that it can be accessed by other processes like analytics and predictions. Data scientists must be able to recognize data models and connect data science resolutions to software development principles for ML scientists.

3. Data analysis

A vital competency for remote ML scientist jobs is the capacity to perform experimental data analysis on a dataset to identify unexpected patterns in data, define specific aberrations, and test ideas. You should be able to generate summary statistics for a dataset, create graphical representations that allow for easy data visualization, clean and prepare data for modeling, perform feature development to obtain more information from the dataset, and so on to improve the ML models, you develop.

4. Models

If you want to get good ML scientist jobs, you'll need to be an expert in machine learning algorithms and know when to use them. Furthermore, you'll need a thorough understanding of complicated algorithms based on artificial neural networks to perform more difficult tasks like picture classification, object identification, face recognition, machine translation, dialogue synthesis, and so on.

5. Services

After determining which machine learning model is best for a given problem, you must decide whether to construct the model from scratch or use existing services. If you need to generate new machine learning models and need a fully managed platform to quickly and efficiently construct, train, and deploy them into a production-ready hosted environment, mastering AWS SageMaker will come in handy.

6. Security

Security management for ML systems, like security management for any other software solution, is an essential task. While substantial data preparation is required for ML models, data access should be limited to just authorized personnel and applications. At all costs, data security is a skill that must be learned.

7. Experience with real-world projects

Recognizing where to apply your technical knowledge to practical tasks and assignments is another important component of becoming an ML scientist. Completing an ML-developing project from start to finish and documenting it in your portfolio can help you sell your talents and knowledge to potential employers and let you get those remote ML scientist jobs that you always wanted.

Interested in remote ML Scientist jobs?

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How to get remote ML scientist jobs?

ML scientists must work hard enough to keep up with all of the industry's recent discoveries and to enhance their skills over time. To excel in their industry, they must follow the best practices successfully and consistently. In this regard, there are some things that scientists should take into account to move forward. They could need help from someone with more experience and who is adept at teaching new abilities. Furthermore, as an ML scientist, you must fine-tune your analytical, programming, and artificial intelligence, and machine learning skills. As a result, the scientists must make certain that someone is on hand to help them and keep track of their progress.

Turing has the best remote ML scientist jobs that fit your ML developing career goals. Working on difficult technical and business problems with cutting-edge technologies will help you grow quickly. Get full-time, long-term remote ML scientist jobs with greater pay and faster career progression by joining a network of the world's greatest scientists.

Why become an ML scientist at Turing?

Elite US jobs
Elite US jobs

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

Career growth
Career growth

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

Exclusive developer community
Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.
Once you join Turing, you’ll never have to apply for another job.

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
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 US firms from the comfort of your home.

Great compensation
Great compensation

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

How much does Turing pay their ML scientist?

Every ML scientist at Turing has the freedom to select his/her rate. On the other hand, Turing will recommend a wage at which we are confident we can offer you a rewarding and long-term opportunity. Our remote ML scientist jobs recommendations are based on our market analysis and demand from our most prestigious clients.

Frequently Asked Questions

Machine Learning engineers benefit from the huge demand in the market. On average, an ML engineer with 3 plus years of experience earns anywhere between $15,000 to $45,000 per annum. If you are searching for a high paying ML job, visit Turing.com. At Turing, you will get a chance to join a community of the world’s best engineers and software developers.

Yes. Machine Learning is one of the top careers in terms of salary, career growth, and general demand. A deep jobs platform like Turing offers the best ML jobs at top U.S. companies. Try taking the Turing tests and work with great companies from anywhere.

It is the combination of our core business model and values that makes us different from others. We provide full-time, long-term projects to remote developers whereas most of our competitors offer more freelance jobs.

Though there are various certifications available to learn Machine Learning that covers ML basics, statistics, Python, Power BI, Open CV, NumPy, etc., the actual career starts when you land a challenging and rewarding job in Machine Learning. Visit Turing.com to fetch such jobs in Silicon Valley startups and tech giants.

We are a Palo Alto-based 'deep' jobs platform allowing talented software developers to work with top US firms from the comfort of their homes. We are led by Stanford alumni and successful A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan.

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.

The significant increase in AI positions in the last couple of years has made ML quite popular. Machine learning engineers are in demand as well as highly paid. Via Turing.com, you can apply for these high paying jobs and get a chance to work with Silicon Valley companies from the comfort of your home.

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.

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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.

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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.

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