Machine Learning Engineer (100% Remote)

Aston Carter•New York, NY

1d•$75 - $75•Remote

About The Position

This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to evaluate complex machine learning scenarios and real-world business use cases. You will develop and validate models, review analytical workflows, and provide expert guidance to ensure solutions are technically sound, scalable, and aligned with practical applications, all within a fully remote and flexible engagement.

Requirements

5+ years of professional experience in Data Science, Machine Learning, Advanced Analytics, Quantitative Research, Data Engineering, or related fields.
Strong proficiency in Python and/or SQL for data analysis, modeling, and workflow development.
Hands-on experience developing, evaluating, or deploying analytical and machine learning models.
Solid understanding of core machine learning concepts and statistical methodologies.
Ability to explain complex technical concepts clearly to both technical and non-technical audiences.
Strong written communication skills for documentation and analytical reporting.
Comfort working independently in a fully remote environment.
Availability for approximately 30–40+ hours per week throughout the engagement.

Nice To Haves

Experience with deep learning techniques and frameworks.
Experience in Natural Language Processing (NLP) applications and methodologies.
Data Engineering experience, including building and maintaining data pipelines and analytical workflows.
Hands-on experience with A/B testing, experimentation design, and causal inference approaches.
Forecasting and time series analysis experience for predictive modeling.
Data visualization skills and familiarity with business intelligence concepts and tools.
Experience with model validation, performance evaluation, and ongoing model monitoring.
Quantitative research experience, including rigorous analytical design and interpretation.
Experience as a Machine Learning Engineer, Data Scientist, or Applied AI professional contributing to strategic technology initiatives.
Ability to align analytical and intelligent systems with real-world applications and business objectives.

Responsibilities

Evaluate complex analytical and machine learning scenarios for technical accuracy, scalability, and business relevance.
Develop, validate, and refine statistical models, predictive analyses, and data-driven solutions that address real-world business problems.
Write, review, and optimize Python and SQL code used in data analysis and machine learning workflows.
Design realistic business and analytics use cases based on professional experience and industry best practices.
Assess modeling approaches, underlying assumptions, and analytical methodologies to ensure robustness and reliability.
Create clear, structured documentation and explanations for complex statistical and machine learning concepts.
Identify opportunities to improve analytical processes, outputs, and decision-support frameworks across projects.
Collaborate within structured project guidelines while managing tasks independently and proactively.
Maintain consistent quality, accuracy, and productivity throughout the engagement.
Provide expert insights on machine learning, deep learning, NLP, experimentation, forecasting, and model validation to support next-generation analytical and intelligent systems.
Communicate technical findings and recommendations effectively to both technical and non-technical stakeholders.