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Machine Learning Flexible Hours Jobs (NOW HIRING)

Machine Learning Engineer

Torrance, CA ยท On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Flexible vacation policy * Equity ITAR Requirements To conform to U.S. Government space technology ...

Machine Learning Engineer

Mclean, VA ยท On-site

$105K - $115K/yr

Flexible PTO * Professional development : CEU and tuition reimbursement How You'll Make an Impact ... As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ...

Machine Learning Engineer

Arlington, VA ยท On-site

$77K - $176K/yr

Job Number: R0242757 Machine Learning Engineer The Opportunity: As an experienced AI and ML ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Machine Learning Engineer

Arlington, VA ยท On-site

$77K - $176K/yr

Job Number: R0242766 Machine Learning Engineer The Opportunity: As an experienced AI and ML ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... We've differentiated ourselves by being fast, flexible, creative and honest . Throw out everything ...

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Machine Learning Flexible Hours information

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$25.5K

$42.6K

$88K

How much do machine learning flexible hours jobs pay per year?

As of Jul 16, 2026, the average yearly pay for machine learning flexible hours in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

Which 5 jobs will survive AI?

Machine Learning roles such as data scientists, AI specialists, and machine learning engineers are expected to persist as AI automates routine tasks but requires human oversight, creativity, and complex problem-solving. Jobs that involve emotional intelligence, complex decision-making, and hands-on skills, like healthcare professionals, educators, and skilled trades, are also likely to endure. Continuous learning and adapting to new tools remain essential for job security in an AI-driven workplace.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation can handle certain tasks, MLEs are essential for creating, optimizing, and overseeing complex models. AI is a tool that complements their work rather than replacing the need for skilled professionals in the field.

What is the difference between Machine Learning Flexible Hours vs Data Scientist Flexible Hours?

AspectMachine Learning Flexible HoursData Scientist Flexible Hours
CredentialsDegree in Computer Science, Data Science, or related field; knowledge of ML frameworksDegree in Data Science, Statistics, or related field; proficiency in data analysis tools
Work EnvironmentTech companies, research labs, startups; project-basedBusiness analytics, research institutions, tech firms; collaborative teams
Industry UsageAI development, automation, predictive modelingData analysis, reporting, strategic decision-making

Both roles often offer flexible hours, but Machine Learning roles focus on developing algorithms and models, while Data Scientists analyze data to inform decisions. The choice depends on your skills and career goals within the data and AI industry.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, innovation, and extensive experience, and may be found in technology companies or research institutions with competitive compensation packages.

What does a machine learning job with flexible hours involve?

A machine learning job with flexible hours typically allows professionals to set their own work schedules instead of adhering to a strict 9-to-5 routine. These roles still require expertise in data analysis, algorithm development, and model training, but provide the freedom to work remotely or during non-traditional hours. Flexible arrangements are common in tech companies and startups, enabling better work-life balance while meeting project deadlines and collaborating with teams virtually.

Which 3 jobs will survive AI?

Machine Learning roles such as data scientists, AI specialists, and machine learning engineers are expected to persist as AI advances, due to their focus on developing, managing, and interpreting complex algorithms. These jobs require specialized skills, programming knowledge, and critical thinking that are difficult for AI to fully replicate. Continuous learning and expertise in tools like Python and TensorFlow enhance job security in this field.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer with flexible hours, and why are they important?

To thrive as a Machine Learning Engineer with flexible hours, you need a solid background in computer science, statistics, and mathematics, often supported by a relevant degree and experience in developing machine learning models. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and cloud computing platforms, as well as relevant certifications, is highly valuable. Strong problem-solving skills, self-motivation, and effective communication help you excel when working independently and collaborating remotely. These skills are crucial for delivering impactful solutions, maintaining productivity, and ensuring successful project outcomes in a flexible work environment.

How do flexible hours impact collaboration and project delivery in a Machine Learning role?

In a Machine Learning role with flexible hours, collaboration is typically managed through asynchronous communication tools and scheduled meetings to ensure team alignment. While this flexibility allows for better work-life balance and can boost productivity, it also requires clear communication and proactive planning to meet project deadlines. Team members often coordinate their core working hours for critical discussions or decision-making, and use shared platforms to track progress and share updates. Adapting to this structure can be a challenge at first, but it often leads to a more autonomous and motivated team environment.
More about Machine Learning Flexible Hours jobs
What cities are hiring for Machine Learning Flexible Hours jobs? Cities with the most Machine Learning Flexible Hours job openings:
What states have the most Machine Learning Flexible Hours jobs? States with the most job openings for Machine Learning Flexible Hours jobs include:
Machine Learning Engineer

Machine Learning Engineer

Capgemini Government Solutions LLC

Washington, DC โ€ข On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


Job description

Capgemini Government Solutions (CGS) LLC is seeking a highly motivated Machine Learning (ML) Engineer with an active security clearance to deliver high-quality code components to power the services, servers, distributed systems, and backend architecture. The successful candidate will have the opportunity to conceive and deliver innovative ML solutions to the U.S. Public Sector to help address critical national and global challenges. This individual will join our Data and AI practice in the DC Metro Area. As a part of the rapidly expanding CGS Data and AI practice, the candidate will also help our clients develop, deploy, and modernize their data estates and pipelines. At Capgemini, we are committed to our staffโ€™s professional development and offer a wide range of training and educational resources. In addition to our internal learning sites, we partnered with Coursera and Degreed to offer our staff the latest courses from academic institutions around the world. We provide education expense reimbursements as well as sponsor seminars, conferences, and certifications. Our practice leaders work with every team member to chart appropriate career paths and goals to ensure that we all stay innovative and transformative, which maximizes our ability to scale up our solutions, keep up with the cutting edge, and bring the art of whatโ€™s possible to the Federal Government. Job Responsibilities As a ML Engineer you will: Deliver high-quality code components that will power the services, servers, distributed systems, and backend architecture for Microsoft products Partner with industry-leading Engineers, Artists, Producers and Designers Incorporate the latest AI, Machine Learning and Computer vision capabilities into the design of Microsoft products and services Drive ML-related solutions based on evaluation of requirements, resources, and alternatives Conduct exploratory data analysis to evaluate data pipelines and construct data stores (structured, semi-structured, and unstructured) as needed to feed frameworks/models Develop custom algorithms, frameworks, and models or leverage available tools, libraries, and applications to solve complex problems Deploy ML solutions and develop methodologies to scale up Present and articulate findings and present solutions to clients and team members Maintain knowledge of advances of ML in industry and academia As needed, collaborate with internal and external stakeholders to identify object detection, optical character recognition, automation, predictive modeling, pattern analysis, natural language processing, fraud detection, and other business cases for using ML Required Qualifications U.S. Citizenship and an active secret level security clearance or higher is required Ability to be at client site full time in Washington, DC Bachelorโ€™s degree or higher in machine learning, data science, statistics, computer science, economics, mathematics, information systems, or similar field preferred Minimum of two (2) years of professional experience with machine learning-delivery responsibilities such as: Deliver high-quality code components to power services, servers, distributed systems, and backend architecture Incorporate the AI, machine learning, and Computer vision capabilities into solutions and services Experience in object detection and computer vision models such as YOLO, MMDetection, R-CNN, SSD, FPN, and RetinaNet Experience programming in languages such as Python, R, Scala, SQL, JavaScript, C/C++, and Java Experience using libraries and frameworks such as TensorFlow, PyTorch, Spark ML/MLlib, and Jupyter Excellent verbal and written communication skills Ability to multi-task and stay flexible in a dynamic work environment Nice to have skills/qualifications Active TS clearance Data Science, ML, AI, or Cloud certifications Experience working in an IT project team following SDLC and DevOps methodologies Experience working with big data distributed programming languages and ecosystems such as Hadoop, MapReduce, Pig, or Kafka Experience with designing and building cloud-based databases, data lakes, and data warehouses Experience using tools such as Azureโ€™s Machine Learning and Cognitive Services; AWSโ€™s SageMaker, Polly and Rekognition; DataRobot; or H2O.ai About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of โ‚ฌ22.1 billion. Get The Future You Want | www.capgemini.com Disclaimer All qualified applicants will be considered for employment based on their skills, and merit. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini. Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is $120k - $180k. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Companyโ€™s sole discretion, consistent with the law. Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractorโ€™s legal duty to furnish information. 41 CFR 60-1.35(c)