Job Title: Machine Learning Engineer w2 role
Location: Philadelphia PA (Onsite 4 days/week at 1800 Arch Street)
Alternate location: Reston VA (for strong candidates)
Duration: Contract
Eligibility: USC GC
Job Summary
We are seeking a hands-on Machine Learning Engineer with 5 years of experience who can design build and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced engineering-focused environment.
Key Responsibilities
- Model Development: Design build train and fine-tune machine learning and deep learning models for real-world use cases
- Production Deployment: Deploy monitor and maintain ML models in production environments
- Data Pipeline Development: Build and optimize scalable data pipelines for ingestion transformation and processing
- Performance Optimization: Evaluate models using metrics like accuracy recall and AUC; optimize for performance and scalability
- Collaboration: Work closely with cross-functional teams including data engineers software engineers and business stakeholders
Required Skills & Qualifications
- 5 years of experience as a Machine Learning Engineer or similar role
- Strong Python programming skills with solid software engineering fundamentals
- Recent and hands-on experience with PySpark (mandatory)
- Experience with machine learning frameworks such as Scikit-learn
- Strong understanding of statistics probability and algorithms
- Experience working with SQL data modeling and large datasets
- Proven track record of deploying ML models into production environments
- Experience with AWS services
Preferred Qualifications
- Experience with MLOps tools such as Docker for model deployment
- Hands-on experience with local Large Language Models (LLMs)
- Familiarity with distributed computing and big data technologies
Interview Process
Round 1 (30 mins Virtual)
- Experience overview
- Technical discussion
- Live coding exercise (Video ON full desktop screen sharing required)
Round 2 (60 mins In-Person Preferred)
- Technical deep dive
- Advanced live coding exercise
Work Environment
- 4 days onsite preferred (Philadelphia office)
- Open to relocation candidates
- Reston VA location may be considered if needed
Job Title: Machine Learning Engineer w2 role Location: Philadelphia PA (Onsite 4 days/week at 1800 Arch Street) Alternate location: Reston VA (for strong candidates) Duration: Contract Eligibility: USC GC Job Summary We are seeking a hands-on Machine Learning Engineer with 5 years of exp...
Job Title: Machine Learning Engineer w2 role
Location: Philadelphia PA (Onsite 4 days/week at 1800 Arch Street)
Alternate location: Reston VA (for strong candidates)
Duration: Contract
Eligibility: USC GC
Job Summary
We are seeking a hands-on Machine Learning Engineer with 5 years of experience who can design build and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced engineering-focused environment.
Key Responsibilities
- Model Development: Design build train and fine-tune machine learning and deep learning models for real-world use cases
- Production Deployment: Deploy monitor and maintain ML models in production environments
- Data Pipeline Development: Build and optimize scalable data pipelines for ingestion transformation and processing
- Performance Optimization: Evaluate models using metrics like accuracy recall and AUC; optimize for performance and scalability
- Collaboration: Work closely with cross-functional teams including data engineers software engineers and business stakeholders
Required Skills & Qualifications
- 5 years of experience as a Machine Learning Engineer or similar role
- Strong Python programming skills with solid software engineering fundamentals
- Recent and hands-on experience with PySpark (mandatory)
- Experience with machine learning frameworks such as Scikit-learn
- Strong understanding of statistics probability and algorithms
- Experience working with SQL data modeling and large datasets
- Proven track record of deploying ML models into production environments
- Experience with AWS services
Preferred Qualifications
- Experience with MLOps tools such as Docker for model deployment
- Hands-on experience with local Large Language Models (LLMs)
- Familiarity with distributed computing and big data technologies
Interview Process
Round 1 (30 mins Virtual)
- Experience overview
- Technical discussion
- Live coding exercise (Video ON full desktop screen sharing required)
Round 2 (60 mins In-Person Preferred)
- Technical deep dive
- Advanced live coding exercise
Work Environment
- 4 days onsite preferred (Philadelphia office)
- Open to relocation candidates
- Reston VA location may be considered if needed
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