WiselyWise

AI/ML Engineer

Vaga remota de AI ML Engineering com fit claro de localização do candidato.

Publicada19 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

Model Development:Design, develop, and implement machine learning models and AI algorithms tailored to industry-specific use cases, particularly in predictive analytics, natural language processing, and computer vision.
Data Processing:Collaborate with data engineers to build and maintain robust data pipelines, ensuring high-quality data is available for model training and deployment.
Algorithm Optimization:Optimize machine learning models for performance, scalability, and accuracy, employing techniques such as hyperparameter tuning, model selection, and feature engineering.
Collaboration:Work closely with data scientists, domain experts, and software developers to integrate AI models into production systems and create end-to-end solutions that meet business objectives.
Model Deployment:Deploy machine learning models into production environments using industry-standard tools and frameworks, ensuring reliability and scalability.
Continuous Improvement:Monitor the performance of AI models post-deployment, making iterative improvements based on feedback and changing business needs.
Innovation:Stay up-to-date with the latest advancements in AI/ML technologies and best practices, and apply this knowledge to drive continuous innovation within the team.
Documentation:Create comprehensive documentation for developed models, algorithms, and processes to ensure knowledge sharing and maintainability.

Education:Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus.
Experience:3+ years of experience in AI/ML engineering, with a proven track record of developing and deploying machine learning models in a production environment.
Technical Skills:
Proficiency in programming languages such as Python, R, or Java.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Strong understanding of data structures, algorithms, and software design principles.
Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models.
Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Analytical Skills:Strong problem-solving skills with the ability to analyze complex datasets and develop innovative AI solutions.
Communication:Excellent verbal and written communication skills, with the ability to collaborate effectively across multidisciplinary teams.

Proficiency in programming languages such as Python, R, or Java.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Strong understanding of data structures, algorithms, and software design principles.
Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models.
Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
Experience with containerization and orchestration tools like Docker and Kubernetes.

Experience with natural language processing (NLP) and computer vision.
Experience with real-time data processing and streaming analytics.
Familiarity with ethical AI practices and the ability to implement AI models responsibly.

Opportunity to work on cutting-edge AI projects that have a tangible impact on critical industries.
Collaborative and innovative work environment.
Competitive compensation and benefits package.
Opportunities for professional growth and continuous learning.

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