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Mid Level Fashion Machine Learning Jobs (NOW HIRING)

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

... junior and mid-level researchers. • Optimizes research processes, workflows, and resource ... Required : • 6 to 8+ years of relevant experience in machine learning research. • Master's, PhD ...

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

They are seeking a Senior Machine Learning Research Scientist to lead the development of advanced ... junior and mid-level researchers. • Optimizes research processes, workflows, and resource ...

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

They are seeking a Senior Machine Learning Research Scientist to lead the development of advanced ... junior and mid-level researchers. • Optimizes research processes, workflows, and resource ...

Provides technical leadership and mentorship to junior and mid-level researchers. * Operational ... Contributes machine learning expertise to drive industry impact. * Strategic Planning and ...

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Mid Level Fashion Machine Learning information

What is the difference between Mid Level Fashion Machine Learning vs Data Scientist?

AspectMid Level Fashion Machine LearningData Scientist
CredentialsBachelor's in Computer Science, Data Science, or related field; experience with machine learning frameworksBachelor's or higher in Data Science, Statistics, or related; often includes certifications in data analysis
Work EnvironmentFashion industry, retail companies, e-commerce platformsVarious industries including finance, healthcare, tech, and retail
Employer UsageDevelops models for trend prediction, inventory management, and personalization in fashionBuilds models for insights, predictions, and data-driven decision making across sectors

While both roles involve machine learning skills, Mid Level Fashion Machine Learning specialists focus on applying these techniques specifically within the fashion industry, whereas Data Scientists work across multiple sectors with broader data analysis responsibilities.

What are the key skills and qualifications needed to thrive as a Mid Level Fashion Machine Learning professional, and why are they important?

To thrive as a Mid Level Fashion Machine Learning professional, you need a solid background in data science, machine learning algorithms, and statistics, often supported by a degree in computer science or a related field. Experience with Python, TensorFlow or PyTorch, and familiarity with fashion-specific datasets and tools are typically required. Strong problem-solving skills, creativity, and communication abilities help translate technical insights into actionable strategies for fashion brands. These competencies enable effective development of models that predict trends, personalize recommendations, and drive innovation in the fast-paced fashion industry.

What are Mid Level Fashion Machine Learning professionals?

Mid Level Fashion Machine Learning professionals are data scientists or machine learning engineers who specialize in applying AI and machine learning techniques to the fashion industry. They typically have a few years of experience and work on projects like trend forecasting, image recognition for apparel, recommendation systems, and inventory optimization. Their responsibilities often bridge the gap between junior staff and senior leadership, involving both hands-on model development and collaboration with cross-functional teams. These roles require a solid understanding of machine learning algorithms, programming skills, and some domain expertise in fashion. As technology transforms the industry, these professionals play a key role in driving innovation and efficiency.

What jobs make $3,000 a month without a degree?

Mid-level fashion machine learning roles typically require specialized skills and often a degree, but entry-level positions in retail, customer service, or freelance fashion consulting can sometimes earn around $3,000 monthly without a degree. Other options include roles like sales associate, stylist, or social media manager in the fashion industry, which may rely more on experience and skills than formal education.

What are common collaborative projects that a mid-level fashion machine learning specialist works on within a design or retail team?

As a mid-level fashion machine learning specialist, you’ll frequently collaborate with designers, merchandisers, and data analysts to develop predictive models for trend forecasting, inventory optimization, or personalized recommendation systems. These projects often require translating creative or business objectives into technical solutions, such as building image recognition tools for cataloging products or analyzing customer purchase patterns. You’ll participate in cross-functional meetings, present findings, and iterate on models based on feedback, making strong communication and teamwork skills essential for success.
Infographic showing various Mid Level Fashion Machine Learning job openings in the United States as of May 2026, with employment types broken down into 87% Full Time, and 13% Nights. Highlights an 100% In-person job distribution.
Machine Learning Engineer - Mid Level

Machine Learning Engineer - Mid Level

Eiden Systems Corporation

Sterling, VA • On-site

Other

Medical, Dental, Vision, Life, Retirement

Posted 27 days ago


Job description

My Account
Job Openings >> Machine Learning Engineer - Mid Level
Machine Learning Engineer - Mid Level
Summary
Title: Machine Learning Engineer - Mid Level ID: 177 Location: Sterling, VA
More about this job >
Description

ESC is seeking a Mid-Level Machine Learning Engineer to support a mission-focused R&D program developing advanced signal detection and classification capabilities for national security applications. This role focuses on designing, training, and deploying ML models capable of identifying complex signals within high-bandwidth sensors and I/Q data streams. The engineer will work closely with researchers and software engineers to transition prototype algorithms into low-latency, edge-deployed operational systems supporting real-world mission environments.

Responsibilities:

  • Design, develop, and optimize machine learning models for signal detection, classification, and anomaly detection within noisy and high-volume data streams
  • Develop and tune deep learning architectures including CNNs, LSTMs, and Transformer-based models for temporal and sequence-based analysis
  • Apply signal processing techniques such as Fourier and wavelet transforms to support feature extraction and model performance
  • Build scalable data pipelines for real-time I/Q stream processing, including buffering, windowing, normalization, and inference workflows
  • Evaluate model effectiveness using advanced performance metrics including ROC/AUC, precision-recall curves, confusion matrices, and other techniques for imbalanced datasets
  • Optimize machine learning models for low-latency execution on edge and embedded hardware platforms
  • Develop modular, maintainable, and testable code using Python, NumPy, PyTorch and/or TensorFlow
  • Support integration with network-attached sensors, hardware abstraction layers, and real-time data sources
  • Collaborate with software engineers, researchers, and mission stakeholders in an agile R&D environment
  • Participate in code reviews, technical discussions, and continuous improvement efforts using GitLab-based development workflows
  • Support containerized application development and deployment using Docker within Linux/Unix environments

Required Qualifications:

  • Experience: 4-7 years of professional experience in machine learning or data science, with at least 2 years focused on sensor-based or temporal data.
  • Education: B.S. or M.S. in computer science, data science, or applied mathematics.
  • Security clearance: Active Top Secret (TS) clearance required. SCI preferred.
  • Hands-on experience developing and deploying machine learning models using PyTorch and/or TensorFlow
  • Strong understanding of machine learning fundamentals, statistics, linear algebra, and probability
  • Experience developing software in Linux/Unix environments
  • Proficiency in Python and scientific computing libraries such as NumPy
  • Experience with version control and collaborative development workflows
  • Experience working with I/Q data streams and real-time inference pipelines

ESC offers a competitive compensation package that includes premium health, dental, and vision insurance, a 401(k) plan with company match, life insurance, short- and long-term disability coverage, and more. We also prioritize work-life balance, supporting our team in maintaining a healthy blend of professional and personal well-being.

PAY TRANSPARENCY NONDISCRIMINATION PROVISION

Eiden Systems Consulting (ESC) is an equal opportunity employer and is committed to creating an inclusive and respectful workplace. ESC does not discriminate against any employee or applicant based on age, color, disability, gender, national origin, race, religion, sexual orientation, veteran status, or any other classification protected by federal, state, or local law.

In accordance with 41 CFR 60-1.35(c), ESC will not discharge or otherwise discriminate against employees or applicants for discussing, disclosing, or inquiring about their own pay or the pay of another employee or applicant. However, employees who have access to compensation information as part of their essential job functions may not disclose the pay of others to individuals who do not have authorized access-unless such disclosure is made (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or legal action (including those conducted by ESC), or (c) as otherwise required by law.

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