AI Machine Learning Engineer

Grand Rapids, MI - USA

Monthly Salary: Not Disclosed

Posted on: 4 hours ago

Vacancies: 1 Vacancy

Job Summary

AI / Machine Learning Engineer Overview

We are seeking a highly skilled AI / Machine Learning Engineer to design build and deploy intelligent systems that enhance decision-making automation and product capabilities. The ideal candidate will have strong experience in machine learning deep learning data engineering practices and cloud-based model deployment.

Key Responsibilities

Develop train and optimize ML and deep learning models using Python and modern frameworks (TensorFlow PyTorch Scikit-learn).
Build scalable end-to-end pipelines for data ingestion preprocessing feature engineering model training validation and deployment.
Research prototype and implement new algorithms for computer vision NLP predictive analytics and generative AI.
Collaborate with data engineers product teams and software developers to integrate ML solutions into production systems.
Deploy and manage models using cloud platforms (AWS GCP Azure) and MLOps tools.
Monitor model performance drift and quality; maintain continuous improvements through retraining and tuning.
Work with large-scale datasets to extract insights and improve predictive accuracy.
Document models experiments and architecture clearly for cross-functional teams.
Ensure ML systems follow best practices for security compliance and ethical AI standards.

Required Skills & Qualifications

Bachelors or Masters degree in Computer Science Data Science AI Machine Learning or related field.
Strong hands-on experience with Python TensorFlow PyTorch Keras Scikit-learn etc.
Solid understanding of machine learning algorithms deep learning architectures (CNNs RNNs Transformers).
Experience with cloud platforms: AWS (SageMaker) GCP (Vertex AI) or Azure ML.
Strong knowledge of SQL data structures algorithms and statistics.
Experience building APIs and deploying ML models using Docker Kubernetes or serverless technologies.
Familiarity with MLOps pipelines MLflow Kubeflow or similar tools.
Ability to work with large datasets and use tools like Spark Databricks or Snowflake.
Excellent problem-solving and analytical skills.

Preferred Qualifications

Experience with Generative AI LLM fine-tuning RAG vector databases (Pinecone FAISS).
Experience in NLP tasks like summarization sentiment analysis entity extraction or embeddings.
Experience with real-time model inference or streaming data (Kafka Flink).
Knowledge of reinforcement learning or optimization techniques.
Publications Kaggle experience open-source contributions.

Soft Skills

Strong communication and documentation skills.
Ability to collaborate with cross-functional teams.
Self-driven curious and highly innovative mindset.
Ability to work in an agile environment.

Benefits (Optionally Add)

Competitive salary and performance bonuses.
Healthcare dental and retirement plans.
Remote/hybrid work options.
Professional development certifications and conference sponsorship.

AI / Machine Learning Engineer Overview We are seeking a highly skilled AI / Machine Learning Engineer to design build and deploy intelligent systems that enhance decision-making automation and product capabilities. The ideal candidate will have strong experience in machine learning deep learning da...

AI / Machine Learning Engineer Overview

Key Responsibilities

Develop train and optimize ML and deep learning models using Python and modern frameworks (TensorFlow PyTorch Scikit-learn).
Build scalable end-to-end pipelines for data ingestion preprocessing feature engineering model training validation and deployment.
Research prototype and implement new algorithms for computer vision NLP predictive analytics and generative AI.
Collaborate with data engineers product teams and software developers to integrate ML solutions into production systems.
Deploy and manage models using cloud platforms (AWS GCP Azure) and MLOps tools.
Monitor model performance drift and quality; maintain continuous improvements through retraining and tuning.
Work with large-scale datasets to extract insights and improve predictive accuracy.
Document models experiments and architecture clearly for cross-functional teams.
Ensure ML systems follow best practices for security compliance and ethical AI standards.

Required Skills & Qualifications

Bachelors or Masters degree in Computer Science Data Science AI Machine Learning or related field.
Strong hands-on experience with Python TensorFlow PyTorch Keras Scikit-learn etc.
Solid understanding of machine learning algorithms deep learning architectures (CNNs RNNs Transformers).
Experience with cloud platforms: AWS (SageMaker) GCP (Vertex AI) or Azure ML.
Strong knowledge of SQL data structures algorithms and statistics.
Experience building APIs and deploying ML models using Docker Kubernetes or serverless technologies.
Familiarity with MLOps pipelines MLflow Kubeflow or similar tools.
Ability to work with large datasets and use tools like Spark Databricks or Snowflake.
Excellent problem-solving and analytical skills.

Preferred Qualifications

Experience with Generative AI LLM fine-tuning RAG vector databases (Pinecone FAISS).
Experience in NLP tasks like summarization sentiment analysis entity extraction or embeddings.
Experience with real-time model inference or streaming data (Kafka Flink).
Knowledge of reinforcement learning or optimization techniques.
Publications Kaggle experience open-source contributions.