> Markdown version of [/jobs/ext/2788001-salesforce-developer](https://www.wearedevelopers.com/jobs/ext/2788001-salesforce-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Salesforce Developer

- **Company:** CareerCircle
- **Location:** Cambridge, MA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $138,600.0 - $234,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Word, Artificial Intelligence, Computer Vision, Big Data, Profiling, Image Analysis, Information Engineering, Linux, Python (Programming Language), Machine Learning, OpenCV, Salesforce.Com, Software Engineering, Supervised Learning, Data Processing, High Performance Computing, Pytorch, Salesforce Lightning, Deep Learning, Scikit Learn, Information Technology, HuggingFace, Free and Open-Source Software, Data Management, Feature Extraction, Software Version Control
- **Published:** September 8, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/all/all/0b3113d2-1a6d-413e-b781-158916a64509

## About the Role

Research
Pipelines
Innovation
Algorithms
Microscopy
Scalability
Phenotyping
Claude Code
Data Science
Benchmarking
Presentations
Deep Learning
Drug Discovery
Image Analysis
Version Control
Decision Making
Data Processing
Computer Vision
Computer Science
Machine Learning
Data Engineering
Medical Research
Feature Learning
Biochemical Assays
Feature Extraction
Image Segmentation
Method Development
Workflow Management
Supervised Learning
Software Engineering
Technical Leadership
High Content Imaging
Scientific Literature
Science Communication
Stakeholder Engagement
Artificial Intelligence
Pharmaceutical Sciences
Hugging Face (NLP Framework)
Python (Programming Language), * PhD in computer science, AI, machine learning, biomedical image analysis, computational imaging, data science, or a related quantitative field, with 3+ years of applied experience in AI for bioimaging and computer vision.

 * Demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.
 * Practical expertise in designing benchmarking and evaluation strategies to compare image analysis methods and guide rigorous, evidence-based model selection.
 * Ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance.
 * Strong proficiency in Python and the scientific deep learning stack (e.g., PyTorch, Hugging Face, Lightning, MONAI), along with hands-on experience using image analysis tools such as scikit-image, OpenCV, napari, Cellpose, StarDist, InstanSeg, and OME-Zarr.
 * Self-motivated experienced contributor who thrives in a collaborative, multidisciplinary environment with biologists, imaging scientists, software engineers, and bioinformatics partners, working with appropriate independence and helping shape project direction through both technical expertise and scientific judgment.
 * Excellent scientific communication and stakeholder engagement skills, including the ability to explain complex AI and image analysis concepts to experimental scientists, project teams, engineers, and non-technical audiences.

Desirable Requirements:

 * Experience developing or adapting foundation models, self-supervised learning approaches, multimodal AI models, or embedding-based analysis methods (e.g., DINO, CLIP, SAM) for biological imaging data.
 * Familiarity with the drug discovery pipeline, phenotypic screening, translational biology models, or pharmaceutical research processes.
 * Demonstrated success in turning project-specific solutions into reusable, scalable workflows or standardized analysis products integrated into enterprise platforms, production pipelines, or user-facing tools.
 * Track record of scientific publication, conference presentations, open-source contributions, or internal technical leadership in AI, computer vision, biomedical image analysis, or related fields.
 * Familiarity with agentic coding tools and AI-assisted development workflows (e.g., Claude Code, Copilot).

## Description

The mission of Novartis is to reimagine medicine, and our team advances that mission by applying advanced image analysis, computer vision, and AI methods to early drug discovery. We partner closely with experimental scientists, disease-area teams, data scientists, bioinformatics experts, and platform engineers to extract meaningful biological insight across diverse imaging modalities (high-content screening, custom microscopy platforms) and biological model systems (cellular assays, co-cultures, organoids, tissue models). To grow this capability, we are seeking a seasoned, innovative, and collaborative data scientist with deep expertise in AI-enabled image analysis to join the Data Science team in Discovery Sciences (DSc) at Novartis Biomedical Research, Cambridge, MA. This role combines hands-on delivery of robust image analysis workflows with advanced AI method development, including biomedical image segmentation, representation learning, foundation models, and scalable deployment. The
successful candidate will embed within the research community as the team's scientific lead for imaging-AI, partnering directly with wet-lab scientists to translate complex biological questions into rigorous, reproducible, and impactful analysis strategies., Internal Job Title: Senior Expert I/II, Data Science, * Lead AI-enabled image analysis strategies for complex biological imaging workflows, acting as the embedded imaging-AI scientific partner working side-by-side with wet-lab scientists to understand emerging assay needs, align approaches with scientific priorities and platform standards, and explain advanced AI concepts in accessible terms.

 * Identify high-impact opportunities where AI can deliver meaningful scientific value and define rigorous benchmarking and evaluation strategies to guide method selection.
 * Develop, validate, and deploy robust image analysis algorithms to characterize cellular, organoid, tissue, and other complex biological phenotypes in high-throughput and high-content imaging data, generating reproducible outputs that support decision-making in drug discovery projects.
 * Drive adoption of advanced AI methods for imaging, including deep learning, vision foundation models, embedding-based phenotyping, segmentation, classification, and multimodal integration, translating state-of-the-art methods into practical, validated workflows that augment expert review and enable scalable interpretation of large, high-dimensional datasets.
 * Contribute to scalable, reusable image analysis workflows in partnership with other data scientists, data engineering, and platform teams, championing best practices across the workflow lifecycle., Biology
Research
Advocacy
Equities
Innovation
Market Data
Life Sciences
Microsoft Word
Time Management
Data Management
Ancient History
Medical Research
Behavioral Health
Scientific Writing
Verbal Communication Skills
+0
Login | JoinContact


## Related Videos

- [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Deepfakes in Realtime - How Neural Networks Are Changing Our World](https://www.wearedevelopers.com/videos/180-deepfakes-in-realtime-how-neural-networks-are-changing-our-world)
- [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker)
- [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning)
- [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps)

## Related Articles

- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)