Effectaive LLC
At Effectaive, we are pioneering the future of mental health support by integrating cutting-edge AI technology with proven psychological practices. Our mission is to provide accessible, personalized, and effective mental health care through our AI therapist platform, helping individuals lead healthier, happier lives. As we continue to grow, we are looking for a skilled AI/ML Engineer to help develop and optimize the AI models that power our innovative platform.
Position Overview:
The AI/ML Engineer will play a key role in developing, fine-tuning, and deploying the machine learning models that form the core of our AI therapist platform. You will work closely with data scientists, product managers, and psychology experts to ensure that our AI delivers effective, ethical, and user-friendly mental health support. This role requires a deep understanding of machine learning, natural language processing (NLP), and a passion for using technology to improve mental health outcomes.
Key Responsibilities:
Model Development:
Design, develop, and implement machine learning models, particularly in the areas of natural language processing (NLP) and deep learning, to enhance the capabilities of our AI therapist platform. Data Pipeline Collaboration:
Work closely with Data Engineers to build and maintain data pipelines that feed the machine learning models, ensuring high-quality, clean, and well-structured data. Model Optimization:
Continuously monitor and refine models to improve accuracy, efficiency, and scalability. Implement techniques such as hyperparameter tuning, model pruning, and optimization. Feature Engineering:
Develop and test new features that can improve model performance, working closely with data scientists and domain experts to identify valuable data inputs. Model Deployment:
Deploy machine learning models into production environments, ensuring they are scalable, reliable, and maintainable. Collaboration:
Work cross-functionally with Product, Design, and Psychology teams to ensure the AI models align with user needs, ethical standards, and psychological best practices. Innovation:
Stay up-to-date with the latest developments in AI/ML and NLP, incorporating cutting-edge techniques into our platform as appropriate. Testing & Validation:
Implement rigorous testing and validation procedures to ensure model accuracy and reliability before deployment. Documentation:
Maintain comprehensive documentation of models, algorithms, and processes to ensure transparency and reproducibility. Qualifications: Experience:
3-5 years of experience in AI/ML engineering, with a strong focus on NLP and deep learning. Experience in the healthcare or mental health space is a plus. Technical Expertise:
Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries (e.g., spaCy, Transformers). Strong programming skills in Python or similar languages. Data Skills:
Solid understanding of data processing, feature engineering, and working with large datasets. Experience with cloud-based data and machine learning services (e.g., AWS, Google Cloud) is a plus. Problem-Solving:
Strong analytical skills and the ability to develop creative, data-driven solutions to complex problems. Collaboration:
Excellent teamwork and communication skills, with the ability to work effectively in a cross-functional environment. Ethical Considerations:
Awareness of ethical considerations in AI, particularly in the context of mental health, and a commitment to building responsible AI solutions. Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Benefits: Competitive salary and equity options Flexible working hours and remote work options Opportunities for professional development and career growth A mission-driven work environment focused on improving mental health Apply for this job
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Design, develop, and implement machine learning models, particularly in the areas of natural language processing (NLP) and deep learning, to enhance the capabilities of our AI therapist platform. Data Pipeline Collaboration:
Work closely with Data Engineers to build and maintain data pipelines that feed the machine learning models, ensuring high-quality, clean, and well-structured data. Model Optimization:
Continuously monitor and refine models to improve accuracy, efficiency, and scalability. Implement techniques such as hyperparameter tuning, model pruning, and optimization. Feature Engineering:
Develop and test new features that can improve model performance, working closely with data scientists and domain experts to identify valuable data inputs. Model Deployment:
Deploy machine learning models into production environments, ensuring they are scalable, reliable, and maintainable. Collaboration:
Work cross-functionally with Product, Design, and Psychology teams to ensure the AI models align with user needs, ethical standards, and psychological best practices. Innovation:
Stay up-to-date with the latest developments in AI/ML and NLP, incorporating cutting-edge techniques into our platform as appropriate. Testing & Validation:
Implement rigorous testing and validation procedures to ensure model accuracy and reliability before deployment. Documentation:
Maintain comprehensive documentation of models, algorithms, and processes to ensure transparency and reproducibility. Qualifications: Experience:
3-5 years of experience in AI/ML engineering, with a strong focus on NLP and deep learning. Experience in the healthcare or mental health space is a plus. Technical Expertise:
Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries (e.g., spaCy, Transformers). Strong programming skills in Python or similar languages. Data Skills:
Solid understanding of data processing, feature engineering, and working with large datasets. Experience with cloud-based data and machine learning services (e.g., AWS, Google Cloud) is a plus. Problem-Solving:
Strong analytical skills and the ability to develop creative, data-driven solutions to complex problems. Collaboration:
Excellent teamwork and communication skills, with the ability to work effectively in a cross-functional environment. Ethical Considerations:
Awareness of ethical considerations in AI, particularly in the context of mental health, and a commitment to building responsible AI solutions. Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Benefits: Competitive salary and equity options Flexible working hours and remote work options Opportunities for professional development and career growth A mission-driven work environment focused on improving mental health Apply for this job
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