Machine Learning Engineer

1 Month ago • 5-8 Years • Artificial Intelligence

Job Summary

Job Description

This remote position seeks an experienced Machine Learning Engineer with 5-8 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. You will collaborate with data scientists, software engineers, and product teams to build scalable ML solutions. Key responsibilities include developing and deploying ML models for various applications (recommendation systems, NLP, predictive analytics), designing scalable data pipelines, working with large-scale data, optimizing models, collaborating with cross-functional teams, staying updated on ML advancements, conducting A/B testing, and ensuring responsible AI practices.

Must have:

5-8 years ML experience
Python, Scala, or Java proficiency
ML frameworks (TensorFlow, PyTorch)
Cloud platform experience (AWS, GCP, Azure)
Data pipeline design & implementation
Model optimization & deployment

Good to have:

NLP, computer vision, reinforcement learning
Containerization (Docker, Kubernetes)
Real-time streaming data & time-series forecasting
Big data technologies (Spark, Hadoop, Kafka)
MLOps and CI/CD pipelines

15 skills required

15 skills required for this role

Add these skills to join the top 1% applicants for this job

deep-learning

java

tensorflow

algorithms

scala

ci-cd

kubernetes

reinforcement-learning

spark

computer-vision

azure

aws

data-structures

python

docker

Job Details

This is a remote position.

Job Summary:

We are seeking an experienced Machine Learning Engineer to join our dynamic team. The ideal candidate will have 5-8 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. You will work closely with data scientists, software engineers, and product teams to build scalable ML solutions that drive business impact.

Key Responsibilities:

Develop and deploy machine learning models for various applications, including recommendation systems, NLP, and predictive analytics.
Design and implement scalable data pipelines and model training workflows.
Work with large-scale structured and unstructured data, ensuring high-quality data processing and feature engineering.
Optimize and fine-tune ML models for performance, accuracy, and scalability.
Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to integrate ML models into production systems.
Stay updated with the latest advancements in machine learning, deep learning, and artificial intelligence.
Conduct A/B testing and evaluate model performance using appropriate metrics.
Ensure responsible AI practices, including model explainability, fairness, and security.

Requirements

Required Qualifications:

5-8 years of experience in machine learning, deep learning, or AI engineering.
Strong programming skills in Python, Scala, or Java.
Proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
Experience with cloud platforms (AWS, GCP, or Azure) for deploying ML models.
Expertise in big data technologies (Spark, Hadoop, Kafka) is a plus.
Experience with MLOps practices, including CI/CD pipelines for ML models.
Solid understanding of data structures, algorithms, and software engineering principles.
Strong problem-solving skills and ability to work independently.

Preferred Qualifications:

Experience with natural language processing (NLP), computer vision, or reinforcement learning.
Familiarity with containerization technologies (Docker, Kubernetes) for model deployment.
Experience in handling real-time streaming data and working with time-series forecasting.
Background in statistics, optimization, or mathematical modeling.