AI Trainer (The Model Whisperer)

Do you have a passion for teaching machines how to think, learn, and adapt? Are you excited by the idea of training AI models to understand and respond to complex data sets, transforming raw data into intelligent insights? If you love fine-tuning algorithms and empowering AI systems to get smarter, then our client has the perfect opportunity for you. We’re looking for an AI Trainer (aka The Model Whisperer) to lead the development, training, and optimization of machine learning models that will drive our AI solutions forward.

As an AI Trainer at our client, you’ll work closely with data scientists, machine learning engineers, and product teams to build, train, and improve AI models. Your expertise will ensure that models not only perform accurately but continue to learn and adapt as they encounter new data. Whether it's for natural language processing (NLP), computer vision, or predictive analytics, you’ll be at the forefront of creating smarter, more robust AI systems.

Key Responsibilities:

1. Develop and Train AI Models:
• Work with data scientists and engineers to design, build, and train machine learning models, including supervised, unsupervised, and reinforcement learning. You’ll develop models for a range of AI applications, such as image recognition, NLP, and recommendation engines.
2. Data Preparation and Labeling:
• Lead the data collection and labeling process, ensuring that AI models are trained with high-quality data. You’ll clean, preprocess, and curate datasets, turning raw data into well-structured inputs for training.
3. Fine-Tune and Optimize Models:
• Experiment with different model architectures, hyperparameters, and optimization techniques to improve model performance. You’ll ensure that models generalize well and perform accurately in production environments, minimizing bias and overfitting.
4. Monitor Model Performance:
• Continuously monitor the performance of models in production, detecting potential drift and retraining models when necessary. You’ll ensure that models adapt to new data and remain robust over time, meeting real-world performance expectations.
5. Collaboration and Cross-Functional Work:
• Collaborate closely with data engineers, software developers, and product managers to ensure that AI models are integrated effectively into products and services. You’ll contribute to the overall architecture and implementation of AI-driven solutions.
6. AI Model Documentation and Education:
• Document the training processes, model architectures, and performance metrics for AI models. You’ll help create guides and resources for team members, enabling others to understand and work with the models you’ve trained.
7. Stay Up-to-Date with AI Advancements:
• Keep current with the latest AI and machine learning techniques, tools, and best practices. You’ll experiment with new approaches and technologies to continually improve the models you work on, ensuring our client stays at the cutting edge of AI development.

Requirements

Required Skills:

• Machine Learning Expertise: Strong knowledge of machine learning techniques, including classification, regression, clustering, deep learning, and reinforcement learning. You have hands-on experience training models with frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Data Preprocessing and Feature Engineering: Expertise in preparing large datasets for machine learning, including data cleaning, normalization, feature extraction, and augmentation. You understand the importance of high-quality data for model performance.
• Optimization and Model Tuning: Experience with fine-tuning models and optimizing hyperparameters to improve accuracy and performance. You know how to experiment with different algorithms and techniques to get the best results from your models.
• Collaboration and Communication: Excellent communication skills, with the ability to work across teams and explain complex AI concepts to non-technical stakeholders. You’re comfortable working with both technical and non-technical collaborators to ensure successful model deployment.
• Model Monitoring and Maintenance: Familiarity with monitoring AI models in production environments, identifying performance issues, and retraining models when necessary to maintain performance.

Educational Requirements:

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field. Equivalent experience in AI training or machine learning is highly valued.
• Certifications or additional coursework in AI, machine learning, or data science are a plus.

Experience Requirements:

• 3+ years of experience in AI training, machine learning, or a related field, with hands-on experience building and training machine learning models.
• Proven track record of training AI models for real-world applications and optimizing them for performance.
• Experience with cloud-based machine learning services and tools (AWS, Google Cloud, or Azure) is a plus.

Benefits

• Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
• Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
• Work-Life Balance: Flexible work schedules and telecommuting options.
• Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
• Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
• Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
• Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
• Tuition Reimbursement: Financial assistance for continuing education and professional development.
• Community Engagement: Opportunities to participate in community service and volunteer activities.
• Recognition Programs: Employee recognition programs to celebrate achievements and milestones.