Remote Machine Learning Ops engineer jobs

We, at Turing, are looking for highly-skilled remote Machine Learning Ops engineers who will be responsible for building the most optimized applications and product features applying high-end ML modeling techniques. Get an opportunity to work with the leading U.S. companies and rise quickly through the ranks.

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Job description

Job responsibilities

  • Build back-end infrastructure, data pipelines, and/or machine learning models
  • Build working ranking models and automate modeling pipelines
  • Collaborate with the data engineers and data scientists on new feature development
  • Design, build and optimize applications containerization and orchestration
  • Participate in automating applications and infrastructure deployments
  • Develop MLOp pipelines to support development, experimentation, CI/CD, verification and validation, and monitoring of AI/ML models
  • Evaluate and learn the latest packages and frameworks in the ML ecosystem

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years experience working as an ML Ops engineer (rare exceptions for highly skilled developers)
  • Extensive experience in machine learning algorithms, especially NLP, and statistics
  • Strong software engineering skills in complex, multi-language systems, including Python
  • Comfort working with Linux administration
  • Experience working with cloud computing and database systems
  • Knowledge of ​​data structures, algorithms, programming languages, distributed systems, and information retrieval
  • Understanding of developing and maintaining ML systems built with open source tools
  • Hands-on expertise in machine learning methodology and best practices
  • Good knowledge of deep learning approaches and modeling frameworks like PyTorch, Tensorflow, Keras, etc.
  • Fluency in the English language for effective communication
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Working experience with Azure or AWS platforms
  • Confidence in individual project management
  • Prior experience in professional services, consulting, or advisory
  • Excellent reasoning, analytical, consultative, and communication skills

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How to become a remote Machine Learning Ops engineer ?

Machine learning is among the most valued skills used in the current software development industry. Companies actively try to bring in developers capable of driving their ML-based projects to improve their primary offerings and related services. Today, developers specializing in machine learning development processes and operations have a lot of opportunities to build a successful career. The right set of skills can help professionals get hired by premier organizations working in the field.

To gain success in the field, developers need to possess a thorough understanding of the responsibilities that come with the role. Having clarity about the role and responsibilities associated with the role can allow developers to prepare and contribute efficiently as a Machine Learning Ops engineer. So, for developers looking to find new opportunities, this guide should help to gain a fair understanding of the role and the requirements. Check out the following sections to learn more about the basic qualifications and responsibilities in detail.

What is the scope of a Machine Learning Ops engineer?

As a Machine Learning Ops engineer, you should aim to constantly scale technical knowledge to build new and performant services. The use of Machine Learning techniques in user-facing solutions has significantly increased over the years and with no signs of slowing down. Opportunities in ML-based development are rapidly increasing as more companies are looking for a specialist with proven experience in the role. ML Ops engineers with relevant industry experience and technical acumen can quickly find new opportunities to work on large-scale and customer-facing solutions.

So, if you’re well versed with the necessary technologies for the role, now would be perfect to take your career to the next level. The best approach to taking your company to the next level is by keeping a tab on the latest opportunities at your shortlisted/preferred organizations. When scouting for new postings, try to look for opportunities that match your professional goals along with a technical skillset capable of driving major processes. The following sections should help you to get clarity about the technical requirements and responsibilities often associated with the Machine Learning Ops engineer roles at top organizations.

What are the responsibilities and roles of a Machine Learning Ops engineer?

When hired as a Machine Learning Ops engineer you can expect your daily responsibilities to tasks related to several development processes. As an ML Ops engineer, you will be expected to take responsibility for different processes associated with the role. You will also need to produce clean and efficient codes and define development strategies (if required) that can help developers to quickly scale existing services..

In addition to the basic technical skills, expect to take up other responsibilities based on the operational structure of the employers. But if you are looking to gather knowledge about the core daily responsibilities of a Machine Learning Ops engineer, you can expect responsibilities like

  • Build back-end infrastructure, data pipelines, and/or machine learning models
  • Build working ranking models and automate modeling pipelines
  • Collaborate with the data engineers and data scientists on new feature development
  • Design, build and optimize applications containerization and orchestration
  • Participate in automating applications and infrastructure deployments
  • Develop MLOp pipelines to support development, experimentation, CI/CD, verification and validation, and monitoring of AI/ML models
  • Evaluate and learn the latest packages and frameworks in the ML ecosystem

How to become a Machine Learning Ops engineer?

Machine Learning Ops engineers are some of the most in-demand professionals in the present software development industry capable of driving new and exciting projects. Professionals aiming to succeed in the role need to possess a certain set of skills along with the required technical knowledge. One of the primary requirements to become a Machine Learning Ops would be a degree in computer science or related fields. This will serve as a strong base for building a career and also give companies a reason to consider you for the role. In addition to the educational qualifications, deep technical know-how of essential technologies and tools related to ML Ops processes will also be required to contribute efficiently.

If you’re looking to take your career ahead as a highly valued Machine Learning Ops engineer, you’ll need to have a certain set of technical expertise. When hiring for such roles, The primary set of skills required to be considered an expert in the domain starts with an understanding of machine learning algorithms, especially NLP, statistics. Developers also need to possess expertise in working with multi-language systems, including the likes of Python. Familiarity with cloud computing and database systems will also enable developers to contribute efficiently in the role. In addition to basic technical knowledge, the ability to build and maintain ML systems built with open source solutions will also help you to get hired.

So, for developers aiming to build a successful career as Machine Learning Ops engineers, try to gain a deep understanding of the basics along with evolving trends in the domain. For a more in-depth look into the requirements, you can check out the following section.

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Skills required to become a Machine Learning Ops engineer

To take a career in software development to the next level working as a Machine Learning Ops engineer, developers need to possess a thorough understanding of key skills. Here’s a list of expertise that should help you to secure a good job.

1. PyTorch and Tensorflow

To find success as a Machine Learning Ops engineer, expertise in working with PyTorch and Tensorflow holds a lot of importance. PyTorch is a popular open-source machine learning framework used by developers globally. The framework is widely used for building applications related to computer vision and natural language processing (NLP). Tensorflow is another end-to-end open-source platform used for building ML solutions. It is also a comprehensive solution offering a wide set of flexible tools and libraries to build services in an agile environment. Both technologies hold a lot of importance in the software development industry, especially with the changing trends. So invest time to scale your knowledge and expertise of working with the frameworks to contribute efficiently as a Machine Learning Ops engineer.

2. Python

To work and build up a career as a Machine Learning Ops engineer, developers need to possess a strong grasp of Python. Probably one of the most widely used programming languages for data-intensive solutions, Python has grown in popularity tremendously over the years. Using Python, businesses primarily build solutions that help to process and analyze data in real-time. Businesses, using such insights can even make well-informed decisions. Python over the years has significant prominence in the global market thereby becoming the preferred choice for data science solutions. It is also often used as the alternative to specialized languages like R for ML processes. For which, professionals looking to contribute as a Machine Learning Ops engineer must develop expertise in working with the language. So keep improving your Python skills to become a successful Machine Learning Ops engineer.

3. Cloud services

Today almost every software and web development process utilizes cloud services in some capacity. A modern alternative to legacy hosting and data storage solutions, the ability to configure, scale, and maintain cloud services is essential. Developers do not only need to possess familiarity with such technologies but rather deep understanding would be more helpful. Currently, there are several options available but AWS and Google Cloud are two of the most popular options. Cloud services do not only allow organizations to part with expensive in-house hosting expenses but also devise more cost-effective development strategies. Having a solid understanding of cloud services should help you to find success as a Machine Learning Ops engineer.

4. Linux administration

Another essential skill set necessary to find success as a Machine Learning Ops engineer is the ability to contribute as a Linux administrator. While building new ML-based services, developers need to invest time and effort in managing Linux-based processes to improve key operations. When working as a Machine Learning Ops engineer, you might have to look into tasks like - installing, monitoring performance and hardware systems, and taking backup. Companies prefer to bring in fresh talent who already possess experience in managing and owning such tasks. So, make sure to keep improving your Linux administration skills to build a successful career as a Machine Learning Ops engineer.

5. Interpersonal skills

The global tech community prefers to work with professionals with confidence and excellent communication skills. Collaborative efforts play a major role in the present industry to ensure efficiency in the operations of a company. Working at top tech firms means interacting and collaborating with people from different backgrounds and cultures, making fluency in the preferred language is even more essential. So, make sure to brush up on your interpersonal and language skills to communicate effectively with your colleagues.

Interested in remote Machine Learning Ops engineer jobs?

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How to get hired as a remote Machine Learning Ops engineer?

Top tech organizations look to hire senior server engineers with experience working in various niches. For which, constantly building up technical skillset and gathering knowledge about requirements of various industries is a must. Along with the knowledge of senior server engineers, developers are also expected to be well-versed in working with related technologies and possess efficient interpersonal skills. Developers with an understanding of user preferences also tend to be a better prospect for organizations.

Turing has quickly become the premier platform for taking careers forward working as a remote Machine Learning Ops engineer. We provide developers opportunities to work on era-defining projects and business problems using state-of-the-art technologies. Join the fastest growing network of the top developers around the globe to get hired as a full-time and long-term remote Machine Learning Ops engineer with the best pay packages.

Why become a Machine Learning Ops engineer at Turing?

Elite US jobs

Long-term opportunities to work for amazing, mission-driven US 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 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

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

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

How much does Turing pay their Machine Learning Ops engineer?

Every Machine Learning Ops engineer at Turing can set their own pricing. Turing, on the other hand, will recommend a salary to the Machine Learning Ops engineer for which we are confident of finding a fruitful and long-term opportunity for you. Our salary recommendations are based on an analysis of market conditions as well as customer demand.

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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Leadership

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.

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briefcase
Staff Software Engineer, AI


About the Client

Founded by engineers from  Stanford, Cisco Meraki, and Samsara, we are one of the fastest-growing Video AI companies in the U.S., transforming standard cameras into powerful AI tools that elevate safety, security, and operations for businesses nationwide. In just four years, we have processed more than 1  billion hours of video, and today ingest more daily new videos than  YouTube. Our industry-leading Video AI agents are changing physical operations and defining what video AI can accomplish for physical  operations. We are challenging and disrupting the $30 billion video surveillance market with a plug-and-play camera agnostic solution that is expanding use-cases beyond traditional security. Our approach has fueled fast adoption across 17 industries, powering nearly 1000  businesses and over 70,000 camera feeds. Our exceptionally talented team has created a high growth trajectory that has attracted almost $100 million in investment from top venture firms, including  Redpoint, Scale Venture Partners, Bessemer, StepStone and Qualcomm.



About the Role

We are looking for like-minded builders. We are an extremely passionate and ambitious team building a company designed to outlast our lifetime. No  matter the role or level, we’re looking for more teammates who share the same  high-performance mindset:

  • Relentless Drive: You have extreme ambition and something to prove. Challenges fuels you. Building isn’t just what you do; it’s who you are.
  • Builder’s Mentality: You  thrive on creating new solutions, not maintaining the status quo. If  you've founded a company, been employee number 1 - 20, or have run a  venture for over two years, we’re especially excited to meet you!
  • High Hustle, High Humility: You combine high IQ with high EQ, a low ego, and an unyielding work ethic that pushes you to be among the best at what you do.

Our cultural pillars guide how we operate. We:

  • Spend Strategically. We maximize resources and minimize waste.
  • Push for Progress. We make decisions, move fast, and celebrate action.
  • Obsess Over Customers: We remove friction and add value to create delight.
  • Trust Our Team: Respect, trust and collaboration are non-negotiable.
  • Act Like Owners: We say what we’ll do, and we do what we say, taking pride and responsibility in our work.
  • Never Stop Having Fun: We’re creating something epic, and we’re having fun doing it.


Who you are

  • You are self-motivated and accountable. You  excel with ownership and autonomy, producing high quality outcomes with  minimal direction and oversight. You have strong intuition on what's  most important to work on, and can focus on the most critical items.
  • You are a balanced visionary. You  contribute to strategy with an ability to see the big picture, while  also appreciating details with a drive to make meaningful, hands-on  contributions.
  • You are a humble expert. You  bring strong expertise and nuanced perspectives on the latest AI  technology, while staying open to new ideas and new ways of doing  things. You focus on getting it right in a team setting, rather than  being right.
  • You strive for the next level. You’re ready to stretch your impact and influence and are ready to take on larger scale challenges and/or act as a mentor.
  • You bring rich AI experience. You  have a strong background in AI, ideally with video processing  experience, however, experienced practitioners in AI can adapt as  necessary. You understand classic deep learning techniques, from YOLO to  transformer models to linear classifiers. Yet, you also have experience  with the latest AI foundation models, from embeddings to LLMs and  prompt engineering.
  • You are a creative thinker and problem solver. You  naturally think outside the box to solve new sets of customer problems,  even with few resources. You have a keen eye and technical frameworks  for setting an AI technical direction based on customer context.
  • You bring high-scale technical excellence. You  deeply understand software design, architecture, big-data processing  pipelines, and best practices on systems design + scalability, code  quality, and data/model design. You appreciate the finer details, such  as edge model optimizations, vector indexes and how they work, or how to  design a maintainable data schema. You’ve designed and led complex  systems, shaped multi-team architectures, and created frameworks that  prevent defects and improve validation across products.
  • You’re a debugging and operational excellence expert. You adopt observability tools, tackle unfamiliar codebases, and develop  resources like runbooks to prevent issues. You have an eye for  impending technical issues or optimization opportunities, and  architectural improvements that could be made to increase overall  engineering productivity.
  • You’re a technical leader. You  understand the skill and personal strengths of team members,  effectively mentoring them and placing engineers into the projects that  make them and the company successful
  • You bring 6+ years in software engineering, with significant expertise in AI plus a strong track record in high-quality system delivery.


Responsiilities

You’ll  play a critical role in advancing our capabilities, using your AI  expertise to drive innovative solutions for businesses with physical  environments—from manufacturing plants to car dealerships. Leading the  design and integration of AI-driven features, you’ll elevate both new  and existing products, focusing on scalable, real-world applications  that improve safety, operations, and efficiency. Working closely with  cross-functional teams, you’ll apply cutting-edge AI techniques to  transform video data into actionable insights that empower our clients.  By setting standards in AI reliability and performance, you’ll ensure  Spot AI’s product suite consistently delivers high-impact outcomes.



What excites you:

  • Working  on and thinking about the latest models across multiple domains, such  as Dinov2, CLIP, GPT4o/Gemini. Applying these models to real world  physical problems to enhance safety, operations, and efficiency.
  • Working  with a datastream of over 200k datapoints and embeddings a second,  wrangling this into actionable insights with fast and accurate queries.
  • Helping  to democratize and educate about the latest foundational models to  customers and team members, helping them share your vision of what AI  can do for the world.
  • Working with a global, several thousand  node distributed hybrid edge-cloud, processing millions of hours of  video a day.A place that gives you the room to learn from failure while  driving excellence.
  • Advancing our AI’s product capabilities  by applying cutting-edge AI techniques, helping transform video data  into powerful, real-world solutions for our clients.
  • Designing  and implementing AI-driven features across new and existing products,  with a focus on scalability and tangible value for diverse industries.
  • Diving  into complex challenges in video intelligence, using your expertise to  bring actionable insights to businesses in physical environments.
  • Collaborating  closely with cross-functional teams to build tools and frameworks that  set a new standard for AI performance and reliability in our industry.
  • Mentoring and guiding other engineers to foster collaboration and innovation that increase project impact.
  • A culture where hard work that drives great outcomes is expected, celebrated, and rewarded.
  • A place where you can make industry-wide impact and contribute to one of the most exciting technologies of our time

Offer Details

  • Full-time contractor (no benefits)
  • Remote only, full-time dedication (40 hours/week)
  • 6 hours of overlap with Pacific Timezone
  • Competitive compensation package.
  • Opportunities for professional growth and career development.
  • Dynamic and inclusive work environment focused on innovation and teamwork
Business Services
11-50 employees
PythonPyTorchTensorflow
briefcase
Senior Java Engineer – Snowflake Integration

Job Title: Senior Java Engineer – Snowflake Integration

Experience: 6–10 Years
Location: Gurugram
Work Mode: Hybrid (3 Days Work From Office)

Job Overview

We are looking for a Senior Java Engineer with strong experience in Java 17+, backend system development, and Snowflake integration, to build and maintain enterprise-grade data and transaction systems in the BFSI domain. The role involves working on high-scale, secure, and compliant platforms handling critical financial data.

Key Responsibilities

  • Design, develop, and maintain scalable backend services using Java 17+
  • Integrate Java applications with Snowflake Data Cloud for analytics and reporting use cases
  • Build and optimize data pipelines between transactional systems and Snowflake
  • Design and consume RESTful APIs for internal and external integrations
  • Ensure data security, governance, and compliance as per BFSI standards
  • Optimize application performance, scalability, and reliability
  • Collaborate with data engineering, DevOps, and product teams
  • Participate in architecture discussions and technical design reviews
  • Support production systems and perform root cause analysis when required

Mandatory Technical Skills

Core Java & Backend

  • Strong hands-on experience with Java 17 or higher
  • Deep understanding of OOP, multithreading, concurrency, and JVM internals
  • Experience with Spring / Spring Boot
  • Strong experience building RESTful microservices
  • Experience with Hibernate / JPA

Snowflake & Data Integration

  • Hands-on experience integrating applications with Snowflake
  • Strong understanding of:
    • Snowflake architecture and data storage concepts
    • Virtual warehouses, databases, schemas
  • Experience using Snowflake connectors (JDBC/ODBC) from Java
  • Knowledge of data ingestion and transformation patterns
  • Understanding of SQL optimization in Snowflake

Databases

  • Strong experience with RDBMS (PostgreSQL / Oracle / MySQL)
  • Advanced SQL skills and performance tuning
  • Experience handling large datasets and analytical queries

Cloud, DevOps & Tools

  • Experience with cloud platforms (AWS / Azure / GCP)
  • Familiarity with Docker and containerized deployments
  • Experience with CI/CD pipelines
  • Working knowledge of Linux environments
  • Experience with version control systems (Git)

BFSI Domain Experience (Mandatory)

  • Proven experience working in Banking, Financial Services, or Insurance
  • Understanding of:
    • Transaction processing systems
    • Data privacy and regulatory compliance
    • Security standards (encryption, access control, auditing)
  • Experience working on high-availability, mission-critical systems

Soft Skills

  • Strong problem-solving and analytical skills
  • Ability to work independently with minimal supervision
  • Excellent communication skills
  • Experience collaborating with cross-functional teams
  • Ownership mindset and attention to detail

Good to Have

  • Experience with event-driven architectures (Kafka / MQ)
  • Exposure to data warehousing or analytics platforms
  • Experience with Agile / Scrum environments
  • Knowledge of financial reporting or risk systems

Ideal Candidate Profile

  • 6–10 years of backend development experience
  • Strong Java 17+ expertise with enterprise application exposure
  • Hands-on Snowflake integration experience
  • Solid BFSI domain background
  • Willingness to work 3 days from Gurugram office
Finance
10K+ employees
Core JavaSpring BootOOP+ 2
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