Machine Learning Engineer Position Available In Capitol Planning Region, Connecticut
Tallo's Job Summary: This job listing has been recently added. Tallo will add a summary here for this job shortly.
Job Description
Machine Learning Engineer
W2 Only
for W2 Candidates
Job Summary:
We are seeking a highly motivated Machine Learning Engineer to join our team. You will be responsible for developing, deploying, and optimizing machine learning models that help solve real-world problems. You will collaborate closely with data scientists, engineers, and product teams to turn data into actionable insights and intelligent systems.
Key Responsibilities:
Design, build, and deploy scalable machine learning models for classification, regression, recommendation, NLP, or computer vision tasks.
Collaborate with data scientists and software engineers to integrate models into production environments.
Optimize model performance using techniques like hyperparameter tuning, feature engineering, and data augmentation.
Evaluate and monitor deployed models to ensure long-term accuracy and relevance.
Stay current with the latest research and industry trends in machine learning and AI.
Develop data pipelines and tools for training and validating machine learning models.
Write clean, maintainable, and well-documented code.
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
Experience working with large datasets and data processing tools (e.g., Pandas, NumPy, SQL, Spark).
Solid understanding of machine learning algorithms and statistical modeling techniques.
Experience with version control (e.g., Git) and software development best practices.
Preferred Qualifications:
Experience deploying ML models using AWS, Azure, or Google Cloud Platform.
Familiarity with MLOps practices and tools like MLflow, Kubeflow, or Airflow.
Knowledge of deep learning architectures (CNNs, RNNs, Transformers).
Exposure to DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
Publications or contributions to open-source ML projects.
Benefits:
Competitive salary and performance bonuses
Flexible work schedule and remote options
Health, dental, and vision insurance
Professional development budget and learning opportunities
Friendly and innovative team environment
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job
Dice Id:
90737436
Position Id:
OOJ – 5310-4314-1749824382