Avatar for Inhabitr
Inhabitr
Actively Hiring
Engineering the future of furniture access!
  • Top 10% of responders
    Inhabitr is in the top 10% of companies in terms of response time to applications
  • Responds within two weeks
    Based on past data, Inhabitr usually responds to incoming applications within two weeks
  • B2C
  • +2

Machine Learning Engineer

Reposted: 1 month ago• Recruiter recently active
Visa Sponsorship

Not Available

Remote Work Policy

In office

RelocationAllowed
Skills
Python
Machine Learning Data Science Python

About the job

About Inhabitr:
Inhabitr is a fast-growing furniture tech company revolutionizing the industry. We offer a unique platform where customers can buy or rent furniture, catering to professionals, students, realtors, and homeowners. Our innovative approach combines technology with furniture solutions to provide unparalleled flexibility and convenience.

Position Overview:
We are seeking a talented Machine Learning Engineer to join our Data Science and Engineering team. This role offers an exciting opportunity to apply your skills in machine learning, computer vision, and MLOps to drive innovation in the furniture tech industry. The ideal candidate will have a strong foundation in deep learning frameworks and cloud technologies, with a passion for developing and deploying AI-driven solutions.

Key Responsibilities:
Develop and implement machine learning models, with a focus on computer vision applications
Design and maintain scalable data pipelines using cloud technologies (AWS, GCP)
Contribute to the end-to-end machine learning lifecycle, from data preparation to model deployment
Collaborate with cross-functional teams to integrate AI solutions into our products
Optimize ML models for performance and scalability
Implement MLOps best practices to ensure efficient model deployment and monitoring

Technical Skills Required:
Strong proficiency in Python, with expertise in deep learning frameworks (PyTorch, Keras, TensorFlow)
Experience with computer vision libraries and techniques
Familiarity with cloud platforms (AWS, GCP) and big data technologies (Spark)
Proficiency in data manipulation and analysis using pandas, numpy, and scikit-learn
Experience with data visualization tools (plotly express, seaborn, matplotlib)
Knowledge of SQL for data querying and manipulation
Familiarity with version control (Git) and containerization (Docker)
Understanding of MLOps principles and practices

Additional Desirable Skills:
Experience with 3D data processing (open3D)
Familiarity with MATLAB
Knowledge of advanced visualization techniques (manim)

Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, or related field
3-5 years of experience in machine learning or software engineering roles
Demonstrated experience with deep learning and computer vision projects
Relevant certifications (e.g., Deep Learning Specialization, MLOps Specialization) are a plus

Personal Attributes:
Strong problem-solving skills and attention to detail
Excellent communication skills and ability to work in a collaborative team environment
Eagerness to learn and adapt to new technologies
Passion for applying AI to real-world problems

What Inhabitr Offers:
A dynamic and collaborative work environment
Opportunities for professional growth and skill development
Competitive salary and benefits package
Chance to make a significant impact in a rapidly growing tech company
Join us in shaping the future of the furniture industry through innovative data solutions!

About the company

Inhabitr company logo

Inhabitr

Actively Hiring
Engineering the future of furniture access!51-200 Employees
Company Size
51-200
Company Industries
B2B · SaaS · Mobile · Artificial Intelligence / Machine Learning
  • Top 10% of responders
    Inhabitr is in the top 10% of companies in terms of response time to applications
  • Responds within two weeks
    Based on past data, Inhabitr usually responds to incoming applications within two weeks
  • B2C
  • B2B
  • Growth Stage
    Expanding market presence
Learn more about Inhabitr image

Funding

AMOUNT RAISED
Undisclosed amount
FUNDED OVER
1 round
Round
S
Undisclosed amount
Seed - Nov 2016

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