Machine Learning Engineer

Skycrew; Las Vegas (NV); On-site; USD 11,000 - 13,000; Part time

Benefits offered by this job

Accommodation provided

Visa sponsorship available

Relocation assistance available

Job summary

Skycrew in Las Vegas is seeking a Machine Learning Engineer to design, develop, and deploy ML models addressing real-world business challenges. You will work with cross-functional teams to gather requirements, clean and preprocess data, and evaluate models for accuracy and performance.

The role emphasizes hands-on modeling in Python/R, familiarity with TensorFlow/PyTorch, and strong communication skills to translate technical findings for stakeholders.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science or related field.
• Experience with Python or R for data manipulation and modeling.
• Strong understanding of ML techniques and algorithms (decision trees, random forests, neural networks).
• Familiarity with TensorFlow or PyTorch is a plus.
• Experience with SQL databases for data retrieval is preferred.
• Excellent problem-solving and communication skills for cross-functional collaboration.

Responsibilities

• Develop and implement machine learning models and algorithms to solve business problems.
• Collaborate with cross-functional teams to gather requirements and identify ML opportunities.
• Perform data cleaning, preprocessing, feature engineering, and model evaluation.
• Build and maintain data pipelines for efficient data processing.
• Perform statistical analysis and apply ML techniques such as classification, clustering, regression.
• Tune hyperparameters to optimize model accuracy and performance.
• Communicate results to non-technical stakeholders clearly.

Skills

Python

R

SQL

Data analysis

Critical thinking

Communication

Problem-solving

Education

Bachelor's or Master's degree in Computer Science or Data Science

Tools

TensorFlow

PyTorch

scikit-learn

Pandas

Job description

We are hiring a Machine Learning Engineer to join our team in Las Vegas, USA. As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex business problems. This role requires strong technical skills in machine learning, data mining, and programming, as well as the ability to work collaboratively with cross-functional teams.

Responsibilities

• Develop and implement machine learning models and algorithms to solve business problems
• Collaborate with cross-functional teams to gather requirements and identify opportunities for using machine learning
• Perform data cleaning, preprocessing, feature engineering, and model evaluation
• Build and maintain data pipelines for efficient data processing
• Perform statistical analysis and apply various machine learning techniques such as classification, clustering, regression, etc.
• Optimize models for accuracy and performance by tuning hyperparameters
• Communicate results and findings to non-technical stakeholders in a clear and concise manner

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science or related field
• Experience with programming languages such as Python or R for data manipulation and modeling
• Strong understanding of machine learning techniques and algorithms such as decision trees, random forests, neural networks etc.
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch is a plus
• Experience with SQL databases for data retrieval is preferred
• Excellent problem-solving skills and ability to think critically about complex problems
• Good communication skills to effectively collaborate with cross-functional teams

Salary: $1100 per month (contract position)

Benefits

• Accommodation: Provided by the company
• Visa sponsorship: Available
• Relocation assistance: Available

This is an exciting opportunity for individuals who are passionate about applying their skills in machine learning to solve real-world problems. We welcome fresh graduates who are eager to learn and grow in this field. Come join us in Las Vegas and be a part of our innovative and dynamic team!