Machine Learning Engineer
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Experience Required:
Posted on:
25 days ago
Vacancies:
1 Vacancy
Job Summary
Machine Learning Engineer
A leading technology services firm is seeking an experienced Machine Learning Engineer to architect and implement advanced ML and AI-driven solutions. This role combines hands-on engineering with leadership requiring deep technical expertise in model development deployment and optimization. The ideal candidate will bring a strong command of modern ML frameworks cloud platforms and generative AI tools like LangChain and RAG.
This position is hybrid and open to local candidates only.
Position Overview
The Machine Learning Engineer will lead the end-to-end lifecycle of machine learning initiativesfrom data pipeline design to production deploymentwhile collaborating across data science engineering and business teams. This is a high-impact role at the intersection of AI innovation scalable architecture and applied data science ideal for engineers passionate about operationalizing ML solutions at scale.
Key Responsibilities
Lead and execute machine learning projects from concept to production ensuring performance scalability and business impact.
Collaborate with data scientists to design implement and optimize ML and AI models.
Partner with infrastructure teams to enhance the architecture stability and scalability of ML platforms.
Design and build optimized data pipelines to support real-time and batch inference.
Extend and maintain existing ML libraries frameworks and APIs to accelerate delivery.
Implement model monitoring governance and automation frameworks for robust ML operations (MLOps).
Drive continuous improvement of ML platform capabilities staying aligned with the latest technologies and best practices.
Translate complex ML and AI solutions into actionable business insights and measurable results.
Provide mentorship and technical direction to junior engineers on the ML team.
Requirements
Required Qualifications
Bachelors degree in Computer Science Engineering or a related field (Masters preferred).
7 years of experience in machine learning or applied AI engineering.
Proficiency in Python Java and Scala with a solid foundation in algorithms data structures and multithreading.
Expertise in ML and DL frameworks such as XGBoost scikit-learn TensorFlow and PyTorch.
Experience with Generative AI LangChain and Retrieval-Augmented Generation (RAG) architectures.
Hands-on experience with cloud-based ML platforms such as AWS SageMaker GCP AI Platform or DataRobot.
Strong understanding of model lifecycle management including containerization real-time inference and CI/CD for ML.
Experience developing and deploying production-grade ML applications on cloud infrastructure.
Familiarity with Agile/Scrum methodologies and collaborative cross-functional teamwork.
Preferred Experience & Skills
Strong knowledge of MLOps practices including monitoring retraining pipelines and governance frameworks.
Experience architecting generative AI solutions for enterprise-scale use cases.
Thought leadership in machine learning innovation model scalability and ethical AI practices.
Excellent communication collaboration and problem-solving skills.
Attributes & Mindset
Analytical thinker with a passion for innovation and applied AI.
Highly detail-oriented with a focus on code quality and model performance.
Self-motivated and capable of leading projects in fast-paced environments.
Committed to continuous learning and staying ahead of emerging ML technologies.
Benefits
Location: Newark NJ (Hybrid)
Experience Level: MidSenior
Employment Type: Contract
Compensation: $60/hour
Required Skills:
7 years of experience in Machine Learning. Extensive software engineering experience with strong working experience as a Machine Learning proficiency with Python Java and Scala. Strong computer science fundamentals such as algorithms data structures multithreading. Experience working with Generative AI using LangChain for Gen AI and techniques like RAG. Experience using ML and DL Libraries:XGBoost SKlearn Tensorflow or PyTorch In-depth experience building solutions using public clouds such as AWS GCP. Experience using ML platforms like SageMaker H2O DataRobot etc. Strong knowledge on ML model development life cycle components like containers batch vs real time inference endpoints application security testing etc. Experience managing relationships in a cross-functional environment with multiple stakeholders. Experience with developing and deploying production-grade applications with ML inferences using automation pipeline on cloud. Experience working in Agile/ Scrum development process. Thought leadership and innovative thinking. Excellent communication and collaboration skills.
Required Education:
Bachelors degree in computer science computer engineering or a related engineering field. Masters degree preferred.
Company Industry
IT Services and IT Consulting
Key Skills
- Industrial Maintenance
- Machining
- Mechanical Knowledge
- CNC
- Precision Measuring Instruments
- Schematics
- Maintenance
- Hydraulics
- Plastics Injection Molding
- Programmable Logic Controllers
- Manufacturing
- Troubleshooting
