At Genmab, we're committed to building extra[not]ordinary futures together, by developing antibody products and pioneering, knock-your-socks-off therapies that change the lives of patients and the future of cancer treatment and serious diseases. From our people who are caring, candid, and impact-driven to our business, which is innovative and rooted in science, we believe that being proudly unique, determined to be our best, and authentic is essential to fulfilling our purpose.

At Genmab, AI technology is more than just a solution, it powers the R&D, Commercial, and functional business units that work tirelessly to save lives and bring valuable treatments to patients around the world. The new data science team, AI and Analytics Products, is building quickly to meet the business demand of immediate, real-time AI technology product innovation. Our technology experts tackle exciting challenges in collaborative teams but work in an environment where individual and career development is always valued. Our team members leverage their talents and passion, building new and innovative products, creating programs founded in automation in agile frameworks, and driving existing and cutting-edge innovation. We are seeking an experienced Product Owner who is passionate about data, with a strong background in data analytics and Artificial Intelligence/Machine Learning (AI/ML) principles. This role is pivotal in driving AI/ML initiatives, shaping product features, and ensuring successful project delivery.

Position Overview:

We are seeking an experienced Machine Learning Engineer to join our team, specializing in Large Language Models (LLMs) and Generative AI. The ideal candidate will have a strong background in AI/ML technologies, with specific expertise in developing, training, and deploying large-scale language models and generative systems. You will play a key role in driving our AI initiatives, contributing to innovative projects, and shaping the future of our AI capabilities.

This is a hybrid role that requires 60% onsite presence in Princeton, NJ

Roles and Responsibilities:
Model Development and Training: Design, implement, and train large-scale language models, deploy machine learning models over the clouds, generative AI algorithms to support a variety of applications, including text generation, content creation, and data synthesis. Deploy the final models to production and monitor their performance and accuracy on regular basis. Conduct machine learning & LLMs tests and experiments, validations, model performance and lifecycle management. Lead CICD process and establish best practices of ML/LLM product deployments over the clouds. Contribute to the ML architecture design, discussion, changes especially over the clouds.
Research and Innovation: Stay abreast of the latest developments in AI/ML, particularly in LLMs and generative AI, and apply cutting-edge research to solve complex problems and improve model performance.
Data Management: Collaborate with data teams to identify, collect, and preprocess large datasets suitable for training and refining LLMs. Work with product owners, data analysts, and data scientists to understand large datasets, preprocess them, and extract features from them.
Performance Optimization: Optimize models for efficiency, scalability, and performance. This includes experimenting with different architectures, tuning hyperparameters, and leveraging hardware accelerations. Train predictive models using the data and analyze their performance to determine which will provide the most accurate results. Fine-tune the models by adjusting hyperparameters, like learning rate and regularization, to improve their accuracy further.
Collaboration and Leadership: Work closely with cross-functional teams, including product managers, software engineers, and data scientists, to integrate AI models into products and services. Provide technical leadership and mentorship to junior team members.
Ethical AI Practice: Ensure models are developed with a commitment to ethical AI principles, addressing issues such as fairness, transparency, and privacy.


Required Qualifications:
Bachelor's or master's degree in computer science, Statistics, or a related field
Strong programming skills in Python, Java, or C
Proficiency with frameworks/libraries like TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LangServe, LangSmith, OpenAI
Proficiency with Transformer models, Autoregressive Models, GPT-3 & 4, Autoencoding Models, BERT, Gemini, ALBERT, ELECTRA, RAGs, Autoencoders, Sequence-to-Sequence Models, hyperparameter tuning, LoRA
Strong understanding of NLP techniques and algorithms.
Minimum of 5 years of experience in machine learning and AI, with a focus on large language models and generative AI.
Versioning control tools, Git, Gitlab, CICD tools, Dockers and Kubernetes
Knowledge of data science, machine learning & deep learning models and expertise in statistics
Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch and other open sources ML frameworks.
Experience with cloud computing platforms such as AWS, Azure, or Google Cloud
Excellent problem-solving skills and attention to detail and ability to work independently.
Proven track record of developing and deploying AI models in a production environment with LLMs capability.


Desired Skills:
PhD in a related field is a plus.
Publications in top AI/ML conferences or journals.
Experience with ethical AI frameworks and bias mitigation techniques.
Strong problem-solving abilities and excellent communication skills.
Ability to work in a fast-paced and dynamic environment.


For US based candidates, the proposed salary...

Equal Opportunity Employer - minorities/females/veterans/individuals with disabilities/sexual orientation/gender identity