Company:
BespokeLabs (VC-backed, founded by IIT & Ivy League leaders)
Type:
Contract | Remote | 20–40 hrs/week | 8–16 weeks
Compensation:
$25–$40/hr
Experience:
5+ years
About BespokeLabs
BespokeLabs is a venture-backed startup founded by seasoned IIT and Ivy League alumni. We specialize in building cutting-edge, AI-driven systems and next-gen digital products. Our mission is to harness advanced machine learning to solve real-world problems with speed, precision, and scale.
We’re looking for a
Machine Learning Engineer
with deep expertise in designing, training, and optimizing models to help accelerate our product roadmap. This is a high-impact contract role for someone who loves experimentation, cutting-edge research, and production-grade ML.
Role Overview
You will be responsible for building ML models end-to-end—from problem framing, exploratory analysis, and feature engineering to experimentation, training, evaluation, and deployment support. You’ll work closely with our product and engineering teams to translate high-level goals into robust ML solutions that can be integrated into real-world applications.
Key Responsibilities
Design, build, and optimize machine learning models for classification, prediction, NLP, recommendation, or generative tasks.
Run rapid experimentation cycles, evaluate model performance, and iterate continuously.
Conduct advanced feature engineering and data preprocessing.
Implement adversarial testing, model robustness checks, and bias evaluations.
Fine-tune, evaluate, and deploy transformer-based models where necessary.
Collaborate with engineering teams to prepare models for production use.
Maintain clear documentation of datasets, experiments, and model decisions.
Stay updated on the latest ML research, tools, and techniques to push our modeling capabilities forward.
Required Qualifications
5+ years of hands-on experience
in machine learning model development.
Proven expertise in building and deploying ML models in a
production ML product company
.
Strong proficiency in
Python
,
PyTorch/TensorFlow
, and common ML/NLP frameworks.
Solid understanding of ML fundamentals—statistics, optimization, model evaluation, architectures.
Experience with distributed training, ML pipelines, and experiment tracking.
Strong problem-solving and algorithmic thinking.
Experience with cloud environments (AWS/GCP/Azure).
Preferred Qualifications
Published research papers (conference or journal).
Strong track record in
Kaggle competitions
(medals or high-ranked submissions).
Experience with LLM fine-tuning, vector databases, or generative AI workflows.
Familiarity with MLOps tools (Weights & Biases, MLflow, Airflow, Docker, etc.).
Experience optimizing inference performance and running models at scale.
What We Offer
Opportunity to work with a world-class founding team and cutting-edge ML projects.
Flexible remote contract (20–40 hours/week).
A fast-paced environment with room for innovation.
Competitive hourly compensation with potential for future collaboration or full-time roles.