Staff /Senior Staff Machine Learning Engineer
Job Description Summary
In pursuit of accelerating the energy transition and recognizing the grid's significance in this transformation,
ThinkLabs AI is introducing Grid Copilot TM , an initiative aimed at realizing the grid of the future. We are seeking
a Staff /Senior Staff Machine Learning Engineer to accelerate the design and delivery of our machine learning
and generative AI models, technology, and cloud engineering, leveraging cloud services, data science
platforms, and automation pipelines for the operationalization of AI/ML-driven solutions at an enterprise scale.
Your extensive hands-on experience and knowledge of artificial intelligence (AI) and machine learning (ML),
along with your proven track record of implementing AI/ML, make you the ideal candidate for this role.
How You’ll Make an Impact:
Design and lead the implementation of robust and scalable data science and machine learning
architecture integrated into the product platform.
Working with the R&D and Data Science teams, deploy prototype models to production.
Re-train and re-deploy models based on quality parameters collected in continuous monitoring.
Define and monitor quality parameters for ML models in production.
Work closely with data science teams to take newly developed models into production.
Optimize the performance, scalability, and reliability of ML Models and generative AI systems.
Design, implement, and evaluate large-scale ML models and generative AI systems in the energy
domain and applications.
Design and implement ML toolchains and data platforms to scale ML solutions in production.
Collaborate with other machine learning engineers, data scientists, and domain experts to understand
the requirements and challenges of natural language processing and generation tasks.
Define best practices for data engineering, feature engineering, and model deployment.
What You Bring:
Master's degree or PhD in Electrical, computer science, power systems, machine learning, natural
language processing, or a related field.
Strong knowledge in mathematical modeling, RNNs, CNNs, Transformers, LSTMs, transfer learning,
reinforcement learning, imitation learning, GANs, and time-series analysis and modeling of dynamic
systems.
Prior experience in operationalizing machine learning workflows.
Hands-on experience with AWS cloud technologies (SageMaker, Apache Airflow, Kubeflow,
ECS/EKS).
Prior experience in the electricity & energy domain is preferred.
Strong experience in developing and deploying large-scale ML Models and generative AI systems
using frameworks such as numpy, scipy, pandas, scikit-learn, TensorFlow, PyTorch, Hugging Face, or
OpenAI)
Proficient in Python and other programming languages for data analysis and machine learning.
Excellent problem-solving, analytical, and communication skills.
Passionate about natural language processing, generative AI, and creating impactful solutions.
