Remote Materials Science Jobs (NOW HIRING)

Work Location: San Jose, California
Shift:
Department: EL-CT CTO
Recruiter:Anthony Melino

This information is for internals only. Please do not share outside of the organization.

Your Role:

The materials discovery cycle is being fundamentally reshaped by AI from how experiments are designed and hypotheses generated, to how results are analyzed and learning is accumulated across thousands of runs. This role owns the AI and discovery half of that transformation at EMD Electronics, leading the programs that put intelligent systems directly in the hands of R&D scientists.

As part of the wider Materials AI portfolio and team, you will inherit live programs with real users and scientists already in motion, and a portfolio that has already demonstrated measurable scientific impact. The mandate is to deepen that impact, extend the AI stack to new material systems and domains, and shape what AI-enabled discovery looks like at EMD Electronics.

• Portfolio of AI-enabled discovery programs spanning co-scientist agents, Bayesian optimization, and sequential learning - deployed across global R&D and expanding to new material systems
• Leadership across programs in Germany and the US, embedded within the broader Materials AI organization
• External partnership agenda: Identifying, evaluating, and structuring collaborations with AI startups, technology providers, and academic groups to bring frontier capabilities into EMD R&D ecosystem
• Long-term AI-for-science vision: generative models and autonomous experimentation connecting EMD Electronics' capabilities to the businesses of Merck KGaA, Darmstadt, Germany (MilliporeSigma and EMD Serono).

Key Responsibilities

• Define and evolve the AI-enabled discovery roadmap, aligned to the Connected Amplified R&D phases
• Own and prioritize the AI discovery program portfolio; manage budget, delivery milestones, and TLB reporting
• Translate technology advances in AI and scientific ML into a sequenced, fundable program agenda

• Foster tight collaboration with the computational modelling and lab digitization sub-teams within Materials AI
• Develop program leads toward greater ownership and scientific ambition

• Scale a deployed multi-agent AI co-scientist from internal platform toward the primary R&D workflow tool for experiment design, documentation, and analysis
• Extend Bayesian optimization capabilities to new material systems and R&D domains; deepen sequential learning workflows and instrument data integration
• Identify and pilot emerging AI approaches, e.g., generative models, autonomous experimentation, where they create genuine scientific leverage

• Build and manage collaborations with AI startups, academic groups, and technology providers; structure engagements that bring frontier capabilities in-house
• Represent EMD Electronics' AI-for-science work externally at conferences and in strategic partnerships
• Connect relevant initiatives across Merck KGaA, Darmstadt, Germany

Who You Are

Minimum Qualifications:

• Advanced degree in computer science, data science, chemistry, materials science, or a related field
• 5+ years in technical leadership or program management in an AI/ML context within chemical R&D
• Hands-on experience with AI/ML i.e. LLMs, Bayesian optimization, or scientific ML in a real deployment context
• Demonstrated track record of building and managing collaborations with external partners, including startups, academic groups, or technology providers.

• PhD in relevant scientific or technical discipline.
• Proficiency in agentic AI architectures, LLM-based systems, and modern machine learning frameworks.
• Familiarity with Bayesian optimization, sequential learning, or computational materials science.
• Background in semiconductor or specialty chemicals R&D; understanding of R&D workflows and scientific data acquired through hands-on laboratory experience.

Preferred Location:

• San Jose California, United States
• Option for remote

Base Pay Range for this position - $200,200-$300,400

The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other perquisites. For more information click here:

The Company is an Equal Employment Opportunity employer. No employee or applicant for employment will be discriminated against on the basis of race, color, religion, age, sex, sexual orientation, national origin, ancestry, disability, military or veteran status, genetic information, gender identity, transgender status, marital status, or any other classification protected by applicable federal, state, or local law. This policy of Equal Employment Opportunity applies to all policies and programs relating to recruitment and hiring, promotion, compensation, benefits, discipline, termination, and all other terms and conditions of employment. Any applicant or employee who believes they have been discriminated against by the Company or anyone acting on behalf of the Company must report any concerns to their Human Resources Business Partner, Legal, or Compliance immediately. The Company will not retaliate against any individual because they made a good faith report of discrimination.