Technical AI Specialist, Bioinformatics & Computational Biology

We build and deliver AI/ML programs for leading organizations across technology, science, and other data-intensive industries. This role is part of our Bioinformatics and Computational Biology portfolio, which spans genomic and sequence data annotation, biomedical literature and evidence curation, protein and molecular data, and the evaluation of AI model outputs where scientific accuracy matters.

We are looking for experienced technical professionals across delivery, quality, and research. Rather than fit you into a predetermined title, we will align the role with your strongest capabilities and experience.

What You'll Own

You will take ownership of complex work from execution through outcomes. Depending on your background, this could include:

• Leading delivery and serving as the technical or client-facing lead for complex programs
• Designing and managing quality frameworks, scientific calibration, and workforce capability
• Building, testing, and evaluating models, data pipelines, and technical solutions
• Translating scientific requirements into clear operational and technical workflows
• Reviewing annotation guidelines and identifying gaps where they do not accurately reflect biological principles
• Analyzing quality and performance data to identify root causes and improvement opportunities
• Working closely with scientists, engineers, and operational teams to resolve technical challenges
• Ensuring that AI-generated or annotated outputs are not only plausible but scientifically correct

This is a hands-on role. You should be comfortable working directly with data, tools, quality results, and technical teams rather than operating purely at a program-management level.

What You Bring

• 8+ years of relevant professional experience, including at least 2 years in AI/ML, data science, or data engineering.
• A degree in Bioinformatics, Computational Biology, Molecular Biology, Biochemistry, Genetics, or a related life science, or a Computer Science/Engineering degree with substantial professional experience in bioinformatics or computational biology.
• A graduate degree is strongly preferred.
• Working knowledge of sequence and omics data, relevant formats and reference resources, biomedical ontologies, and literature curation.
• Practical experience using Python or R to work with biological data.
• Working knowledge of model training and fine-tuning, LLM delivery, model evaluation, and MLOps.
• Strong scientific judgment and the ability to distinguish technically plausible outputs from biologically accurate ones.
• Strong analytical, problem-solving, and stakeholder management skills.

Certification Requirements

Certification requirements depend on the track:

• Delivery: PMP, PgMP, PRINCE2, or Lean Six Sigma Green Belt or higher
• Quality: Lean Six Sigma Green Belt or higher
• Research: No project management certification required. We will assess your scientific and technical record instead.
• All tracks: AWS, Azure, or Google Cloud certification is an advantage, particularly for candidates working in cloud, MLOps, or AI environments.

Hiring Process

Shortlisted candidates will complete an English proficiency assessment and SHL assessment as part of the selection process.

Innodata is an equal opportunity employer. We welcome candidates from diverse backgrounds and provide reasonable accommodation throughout the hiring process.