⚠ This position is no longer accepting applications.
View open positions →
Bio-ML/AI Engineer
ChordexBio
Full-time Closed
📍 Philippines (Ilocos, NCR, Cebu, Davao) / Remote 📅 Deadline: 15 Apr 2026
About This Position
ChordexBio is seeking a talented and forward-thinking AI Engineer to join our full-time, remote-first team and lead the development and integration of artificial intelligence and machine learning capabilities across our life sciences platform ecosystem. This is a position built for someone who is as excited about the biology as they are about the model — an engineer who sees AI not as a layer on top of a product, but as the engine that makes intelligent, scalable, and transformative science platforms possible.
In this role, you will architect, build, and deploy AI and ML systems that power features across Receptorix, ReceptoCraft, 4labs, and Continuity by Plethory — from predictive modeling and natural language interfaces to automated research workflows and intelligent data management. You will work at the boundary of software engineering and applied science, translating biological and operational research needs into production-grade AI systems. This role is ideal for engineers who have worked in — or are deeply curious about — the life sciences, healthcare, or research technology space. Our ideal AI Engineer is not just technically proficient but is scientifically literate: someone who can engage meaningfully with biological concepts, understand what researchers actually need from intelligent systems, and build accordingly. You should be as comfortable discussing receptor binding predictions as you are optimizing a transformer fine-tuning run.
In this role, you will architect, build, and deploy AI and ML systems that power features across Receptorix, ReceptoCraft, 4labs, and Continuity by Plethory — from predictive modeling and natural language interfaces to automated research workflows and intelligent data management. You will work at the boundary of software engineering and applied science, translating biological and operational research needs into production-grade AI systems. This role is ideal for engineers who have worked in — or are deeply curious about — the life sciences, healthcare, or research technology space. Our ideal AI Engineer is not just technically proficient but is scientifically literate: someone who can engage meaningfully with biological concepts, understand what researchers actually need from intelligent systems, and build accordingly. You should be as comfortable discussing receptor binding predictions as you are optimizing a transformer fine-tuning run.
Responsibilities
1. Design, develop, and deploy machine learning and AI models that power intelligent features across ChordexBio platforms — including predictive analytics, natural language processing, biological data interpretation, and automated workflow assistance.
2. Build and maintain scalable AI/ML pipelines from data ingestion and preprocessing through model training, evaluation, deployment, and monitoring.
3. Collaborate with the bioinformatics, product, and platform engineering teams to integrate AI capabilities into ChordexBio's software ecosystem in a way that is biologically meaningful and scientifically rigorous.
4. Develop and fine-tune large language models (LLMs) or domain-adapted models for life sciences applications — including research assistance, document intelligence, and scientific Q&A interfaces.
5. Implement and optimize computer vision, graph neural networks, or structure-based models where relevant to biological data — such as protein structure prediction, receptor modeling, or construct design.
6. Establish best practices for model versioning, experiment tracking, reproducibility, and AI system documentation across ChordexBio's engineering environment.
7. Evaluate and integrate relevant open-source models, foundation models, and third-party AI tools into ChordexBio's platform stack where appropriate.
8. Contribute to the ethical and responsible deployment of AI in scientific contexts — ensuring transparency, explainability, and accuracy standards are maintained.
9. Monitor the rapidly evolving AI and life sciences AI landscape to identify techniques, tools, or models relevant to ChordexBio's roadmap.
10. Participate in product planning, technical reviews, and cross-functional discussions to ensure AI capabilities are developed in alignment with real research needs.
2. Build and maintain scalable AI/ML pipelines from data ingestion and preprocessing through model training, evaluation, deployment, and monitoring.
3. Collaborate with the bioinformatics, product, and platform engineering teams to integrate AI capabilities into ChordexBio's software ecosystem in a way that is biologically meaningful and scientifically rigorous.
4. Develop and fine-tune large language models (LLMs) or domain-adapted models for life sciences applications — including research assistance, document intelligence, and scientific Q&A interfaces.
5. Implement and optimize computer vision, graph neural networks, or structure-based models where relevant to biological data — such as protein structure prediction, receptor modeling, or construct design.
6. Establish best practices for model versioning, experiment tracking, reproducibility, and AI system documentation across ChordexBio's engineering environment.
7. Evaluate and integrate relevant open-source models, foundation models, and third-party AI tools into ChordexBio's platform stack where appropriate.
8. Contribute to the ethical and responsible deployment of AI in scientific contexts — ensuring transparency, explainability, and accuracy standards are maintained.
9. Monitor the rapidly evolving AI and life sciences AI landscape to identify techniques, tools, or models relevant to ChordexBio's roadmap.
10. Participate in product planning, technical reviews, and cross-functional discussions to ensure AI capabilities are developed in alignment with real research needs.
Requirements
REQUIREMENTS:
1. Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Biomedical Engineering, Computational Biology, or a closely related field — Bachelor's required; Master's or PhD is a strong advantage
2. Strong proficiency in Python and hands-on experience with ML/AI frameworks including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, or equivalent
3. Demonstrated experience building, training, and deploying machine learning or deep learning models in a production or research environment — minimum 2 years preferred
4. Familiarity with LLM architectures, fine-tuning methodologies (LoRA, RLHF, instruction tuning), prompt engineering, and retrieval-augmented generation (RAG) systems
5. Experience with MLOps tooling — including experiment tracking (MLflow, Weights & Biases), model registries, containerization (Docker), and cloud deployment (AWS, GCP, or Azure)
6. Comfort with biological or scientific data types — including sequences, structures, omics datasets, or scientific literature corpora — is a significant advantage
7. Strong software engineering fundamentals: version control (Git), clean code practices, API design, and collaborative development workflows
8. Clear written and verbal communication in English — ability to explain AI systems and results to both technical teammates and non-technical scientific stakeholders
QUALIFICATIONS:
You are an ideal candidate if you are or have experience as:
1. An AI or ML engineer with applied experience in life sciences, healthcare AI, drug discovery, computational biology, or research technology platforms
2. A research scientist or ML researcher with publications or projects in biological sequence modeling, protein structure prediction, or scientific NLP
3. A full-stack AI engineer who has built end-to-end intelligent features — from data pipeline to deployed model to user-facing interface — in a startup or product environment
4. A data scientist or computational researcher transitioning into AI engineering, with strong domain knowledge in STEM and a growing engineering toolkit
5. A software engineer with deep curiosity about biology and AI who has independently pursued projects, courses, or contributions at their intersection
1. Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Biomedical Engineering, Computational Biology, or a closely related field — Bachelor's required; Master's or PhD is a strong advantage
2. Strong proficiency in Python and hands-on experience with ML/AI frameworks including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, or equivalent
3. Demonstrated experience building, training, and deploying machine learning or deep learning models in a production or research environment — minimum 2 years preferred
4. Familiarity with LLM architectures, fine-tuning methodologies (LoRA, RLHF, instruction tuning), prompt engineering, and retrieval-augmented generation (RAG) systems
5. Experience with MLOps tooling — including experiment tracking (MLflow, Weights & Biases), model registries, containerization (Docker), and cloud deployment (AWS, GCP, or Azure)
6. Comfort with biological or scientific data types — including sequences, structures, omics datasets, or scientific literature corpora — is a significant advantage
7. Strong software engineering fundamentals: version control (Git), clean code practices, API design, and collaborative development workflows
8. Clear written and verbal communication in English — ability to explain AI systems and results to both technical teammates and non-technical scientific stakeholders
QUALIFICATIONS:
You are an ideal candidate if you are or have experience as:
1. An AI or ML engineer with applied experience in life sciences, healthcare AI, drug discovery, computational biology, or research technology platforms
2. A research scientist or ML researcher with publications or projects in biological sequence modeling, protein structure prediction, or scientific NLP
3. A full-stack AI engineer who has built end-to-end intelligent features — from data pipeline to deployed model to user-facing interface — in a startup or product environment
4. A data scientist or computational researcher transitioning into AI engineering, with strong domain knowledge in STEM and a growing engineering toolkit
5. A software engineer with deep curiosity about biology and AI who has independently pursued projects, courses, or contributions at their intersection
Benefits & Perks
As a full-time AI Engineer at ChordexBio, you will receive a competitive compensation package commensurate with your experience, technical depth, and demonstrated impact. In addition, you will gain:
1. A technically ambitious role at a programmable biology company where AI is not an afterthought — it is central to what we are building
2. Direct influence over ChordexBio's AI architecture, model strategy, and intelligent platform features from an early and formative stage
3. Collaboration with bioinformaticians, research consultants, and platform teams who bring deep scientific context to every engineering decision
4. Access to ChordexBio platforms, computational resources, and a growing internal dataset ecosystem relevant to your work
5. A fully remote, work-from-home arrangement with flexible scheduling built around engineering excellence, scientific impact, and personal autonomy
---BMAE v1.0.2026
1. A technically ambitious role at a programmable biology company where AI is not an afterthought — it is central to what we are building
2. Direct influence over ChordexBio's AI architecture, model strategy, and intelligent platform features from an early and formative stage
3. Collaboration with bioinformaticians, research consultants, and platform teams who bring deep scientific context to every engineering decision
4. Access to ChordexBio platforms, computational resources, and a growing internal dataset ecosystem relevant to your work
5. A fully remote, work-from-home arrangement with flexible scheduling built around engineering excellence, scientific impact, and personal autonomy
---BMAE v1.0.2026