Machine Learning Engineer

7 Months ago • 5-8 Years

Research Development

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.

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

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

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

cross-functional

data-analytics

forecasting-budgeting

data-structures

alphabeta-testing

mathematical

aws

azure

hadoop

spark

model-deployment

data-science

scikit-learn

pytorch

deep-learning

reinforcement-learning

computer-vision

ci-cd

docker

kubernetes

python

algorithms

scala

tensorflow

java

machine-learning

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.