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Flexible Machine Learning Jobs (NOW HIRING)

Itransition Group

NY · On-site

We are looking for a Machine Learning Researcher to design, develop, and evaluate predictive models ... Flexible working hours aligned to your schedule #J-18808-Ljbffr

Aston Carter

Machine Learning Engineer

Manhattan, NY · On-site

$125/hr

... flexible engagement. Responsibilities * Evaluate complex analytical and machine learning scenarios for technical accuracy, scalability, and business relevance. * Develop, validate, and refine ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In ... Generous PTO and flexible hybrid work model * 401(k) with employer contribution * Professional ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Flexible work schedule * Tuition support * PTO and paid holidays Visit us: www.covar.com

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Flexible PTO with a strong culture of taking it * Weekly team lunches with dietary accommodations

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Flexible PTO with a strong culture of taking it * Weekly team lunches with dietary accommodations

Qfanalytics

Machine Learning Engineer

Miami, FL · On-site

$100 - $125/hr

The Machine Learning Researcher should be interested in Financial Markets, and will be directly ... What We Have To Offer Flexible work arrangements when in office (including working from home ...

Qfanalytics

Machine Learning Engineer

Chicago, IL · On-site

$100 - $125/hr

The Machine Learning Researcher should be interested in Financial Markets, and will be directly ... What We Have To Offer Flexible work arrangements when in office (including working from home ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Flexible in working extended hours. The above statements are intended to describe the general ...

Speria

Machine Learning Engineer

Atlanta, GA · On-site

... flexible and rewarding atmosphere. We pride ourselves for having a working atmosphere that ... Job Summary We are seeking a highly skilled and motivated Machine Learning Engineer to join our ...

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Flexible in working extended hours. The above statements are intended to describe the general ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... Flexible Time Off * Career Development & Mentoring Programs * Health & Wellness Benefits, including ...

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Flexible Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do flexible machine learning jobs pay per year?

As of Sep 10, 2026, the average yearly pay for flexible machine learning 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.

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

AspectFlexible Machine LearningData Scientist
CredentialsTypically requires knowledge of machine learning, programming, and data analysis; certifications like AWS, Google Cloud are commonRequires degrees in statistics, computer science, or related fields; certifications like Certified Data Scientist are beneficial
Work EnvironmentOften in tech companies, startups, or consulting firms; involves building adaptable ML modelsIn various industries including finance, healthcare, and tech; focuses on data analysis and insights
Industry UsageUsed in AI development, automation, and predictive modelingApplied in business analytics, research, and strategic decision-making

Flexible Machine Learning professionals focus on developing adaptable ML models across diverse applications, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary focus and industry usage differ slightly.

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Flexible Machine Learning jobs near you
Infographic showing various Flexible Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, and 3% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning

NY • On-site

Itransition Group
IT Services • 1 - 5K employees
Learn more about Itransition Groupexternal

Other

Re-posted 5 days ago

Job description

We are looking for a Machine Learning Researcher to design, develop, and evaluate predictive models for financial markets. You will work at the intersection of quantitative research, machine learning, and real-world trading constraints, contributing to alpha generation and risk modeling.

office remote Poland

Requirements
  • 3+ years of relevant experience
  • Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow)
  • Hands‑on experience working with tabular/time series data with usage of ML
  • Solid understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross‑validation
  • Knowledge of statistical methods and probability theory
  • Experience with experiment design and offline evaluation
  • Ability to work with large datasets and build efficient data processing pipelines
  • Familiarity with SQL and data querying
  • Strong analytical and problem‑solving mindset
  • Ability to clearly communicate findings and trade‑offs
  • Ownership of tasks from research to implementation
  • Curiosity and willingness to explore new approaches
  • Level of English enough for efficient technical and business communication with native speakers
Nice to have
  • Experience in financial machine learning, quantitative finance, or trading systems
  • knowledge of signal generation, alpha research, portfolio construction or risk modeling
  • Experience with: Deep learning for tabular/time series data (Transformers, RNNs, etc.); Probabilistic modeling or Bayesian methods
  • Hands‑on experience with production ML systems (MLOps, monitoring, retraining)
  • Ability to define research direction and identify high‑impact opportunities
  • Ability to translate business problems into ML solutions
Responsibilities
  • Develop and validate machine learning models for financial time series and cross‑sectional data
  • Conduct research on alpha signals, feature engineering, and predictive modelling techniques
  • Design experiments and backtesting frameworks with proper statistical rigor
  • Work with large‑scale structured and unstructured financial datasets
  • Collaborate with engineering teams to deploy models into production pipelines
  • Analyze model performance, stability, and robustness under changing market conditions
  • Improve data pipelines, labeling strategies, and evaluation methodologies
We offer
  • Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota
  • Competitive compensation that depends on your qualification and skills
  • Career development system with clear skill qualifications
  • Flexible working hours aligned to your schedule
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