**About Ensemble AI:**
At Ensemble AI, we are pioneering a revolutionary approach to representation
learning. Our innovative technology and ML algorithms redefine embeddings,
enabling ML practitioners to harness high-quality data representations
effortlessly and across domains. Ensemble’s product Dark Matter drops into any
existing ML pipeline, enhancing performance with a multilatent representation.
Our technology is industry agnostic and can provide richer insights for deep
learning models. Join us in transforming the ML landscape at Ensemble.
We are a Seed-stage company backed by Salesforce Ventures, M13, Motivate, and
Amplo.
**Job Overview:**
We are seeking a Senior Machine Learning Engineer with expertise in multi-
modal machine learning, particularly integrating image, text, tabular, and
time series data. The ideal candidate will have a solid track record of
designing, researching, and deploying multi-modal models in production
environments. This role blends cutting-edge algorithmic research with
practical deployment, requiring strong collaboration across teams and client
projects. Previous experience in NLP, computer vision, and embedding models is
a plus, with an emphasis on building scalable, multi-modal solutions.
**Key Responsibilities:**
* Design and implement multi-modal machine learning models, integrating data from text, images, tabular, and time series sources.
* Work on embedding models and representation learning for a variety of data types, with an emphasis on multi-modal approaches.
* Develop and enhance core multi-modal algorithms, improving efficiency and scaling for production systems.
* Create new product features based on client needs, driving innovation and expanding the functionality of Ensemble's algorithms.
* Collaborate with cross-functional teams and clients to integrate multi-modal ML models into production systems, optimizing for performance and scalability.
* Drive research and development of frontier ML methods that push the boundaries of AI.
* Manage and scale models on GPU clusters and integrate with cloud platforms like AWS.
* Contribute to future work involving image and text data, though prior CV/NLP experience is a plus.
**Requirements:**
* Strong experience with multi-modal machine learning, particularly combining text, image, tabular, and time series data.
* Proven track record of deploying multi-modal ML models into production environments, with evidence of impact in industry settings (e.g., publications in top-tier conferences and journals).
* Expertise in representation learning and applying it to multi-modal real-world problems.
* Advanced degree (Master's or PhD) in Computer Science, Engineering, Mathematics, Physics, or related field with a focus on machine learning research.
* 5+ years of hands-on experience designing and deploying machine learning models.
* Strong proficiency in Python and familiarity with ML libraries such as TensorFlow, PyTorch, and scikit-learn.
* Experience with AWS and cloud-based machine learning deployments.
**Preferred Qualifications:**
* Experience with cutting-edge multi-modal algorithms, particularly for production-level systems.
* Experience in scaling models across GPUs and optimizing performance.
* Familiarity with MLOps tools and product integrations for multi-modal systems.
* Startup experience with a passion for driving innovation and working in a fast-paced environment.
* Collaborative mindset, especially in a research-to-production workflow.