Home › Companies › Constructivebio › Machine Learning Research Engineer
Machine Learning Research Engineer
Constructivebio · Cambridge, Cambridgeshire, CB22 4WL, United Kingdom · On Site · Active · BambooHR
Job facts
| Field | Value |
|---|---|
| Company | Constructivebio |
| Title | Machine Learning Research Engineer |
| Normalized title | - |
| Department / team | R&D |
| Location | Cambridge, Cambridgeshire |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | BambooHR |
| Posted / first seen | 2026-03-26 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Constructivebio. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through BambooHR. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Cambridge. | Open |
| Department jobs | Active postings in R&D. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Constructivebio |
| Source | 60069fb1-45f2-4e44-8651-c83dc1a5e008 |
| ATS provider | BambooHR |
Description
Constructive Bio is a VC-backed biotechnology startup based in Whittlesford, Cambridge. Our unique technology turns living cells into biofactories, creating sustainable new materials and therapeutics. With full control of the genetic sequence and code, we are exploring chemical space previously unreached by natural biology.
Constructive Bio is a spinout from Professor Jason Chin's laboratory at the MRC Laboratory of Molecular Biology in Cambridge. Learn more about the Chin lab achievements here:
https://www2.mrc-lmb.cam.ac.uk/ccsb/jason-chin/
We recently secured $58 million Series A fundraising. Read more here: https://www.constructive.bio/blog/news/constructive-bio-secures-58-million-in-series-a-financing
What we’re looking for:
We're looking for an ML engineer who can turn prototypes into production systems and work fluidly across the biology-ML boundary. You'll build and maintain our codebase, scale training pipelines, and fine-tune state-of-the-art sequence models on in-house data — all in close collaboration with experimental biologists. This is a frontier role: generative models that directly inform wet-lab design cycles.
As our second ML hire, you'll work directly with our ML Scientist to define engineering standards and infrastructure that will shape everything that follows. The role carries real ownership — and real exposure to the full stack of modern biological ML.
Responsibilities
Implement and benchmark state-of-the-art sequence models (transformers, diffusion models, language models for genomics)
Build robust experimentation infrastructure: logging, dashboards, hyperparameter sweeps, reproducibility tooling
Apply fine-tuning protocols on internal biological datasets
Refactor research code into clean, modular, maintainable systems
Identify technical gaps and propose solutions — distributed training, data pipelines, inference optimization
Translate model outputs into formats biologists can interpret and act on; participate actively in cross-functional discussions
Write well-documented code; participate in code reviews and help set the engineering bar
Requirements
BSc or MSc in an engineering discipline, with demonstrated ML research and development experience
Hands-on production experience with PyTorch and Hugging Face libraries
Solid grasp of algorithms, data structures, and software design principles
Strong communication skills — you're comfortable explaining technical tradeoffs to non-ML collaborators
Curiosity about biology; willingness to engage seriously with the domain, not just tolerate it
Desirable
Experience in computational biology, particularly sequence or genomic language models
Publications or open-source contributions in ML or bioinformatics
Why Constructive Bio
We're a small, focused team building toward a programmable biomolecules platform. As an early joiner you'll have genuine influence over technical direction, not just execution of a pre-set roadmap. You'll work at the intersection of cutting-edge ML and experimental biology, with direct line of sight from model to experiment to result.
We measure success by what works in the wet lab, not what looks good on a benchmark. You'll work directly with experimental scientists to design and test ideas, with a short feedback loop between computation and experiment. That proximity is what makes the work meaningful and demanding. Your models will be evaluated by people who understand the biology deeply, which raises the bar for what good looks like. You'll have a peer in our ML Scientist from day one, but the role requires genuine scientific engagement, not just technical execution.
We offer:
Newly fitted dedicated site in Whittlesford near Cambridge – on-site parking and regular trains to Cambridge, London and Norwich
Competitive salary
Employee share option plan
25 days holiday plus bank holidays
Private health insurance
Pension plan (matching up to 8%)
Collaborative and pioneering environment, at the leading edge of synthetic genomics and engineered translation
We want to build a team with trust and respect for each other and create a culture of collaboration, openness, curiosity, and scientific excellence.
We are built on three principles:
We imagine:
We think big and plan our own path for success.
We pioneer:
We take action and grow together as one to break moulds.
We deliver:
We take ownership and work together to deliver excellence.
Constructive Bio is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Full job record
| Job ID | 2bf8e164f44ee8cf648d757e7346314db18ee448 |
| Org ID | 9977c51f-45ab-4d07-b8f1-032fe7ebd560 |
| Source ID | 60069fb1-45f2-4e44-8651-c83dc1a5e008 |
| Board ID | 60069fb1-45f2-4e44-8651-c83dc1a5e008 |
| Provider | bamboohr |
| Provider Job Key | 101 |
| Title | Machine Learning Research Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Cambridge, Cambridgeshire, CB22 4WL, United Kingdom |
| Department | R&D |
| Team | — |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | — |
| Region | Cambridgeshire |
| City | Cambridge |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://constructivebio.bamboohr.com/careers/101 |
| Apply URL | https://constructivebio.bamboohr.com/careers/101 |
| First Seen At | 2026-05-30 05:50:20Z |
| Last Seen At | 2026-06-06 10:27:06Z |
| Last Checked At | 2026-06-06 10:27:06Z |
| Last Changed At | 2026-05-30 05:50:20Z |
| Inactive At | — |
| Source Posted At | 2026-03-26 00:00:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=constructivebio/date=2026-06-06/2026-06-06T10-27-05-075Z-288b43c36cf6279bc127720a68d7b675e7511d364f3b2a7710df49a5c424d2d7.json |
Event Fields
{
"content_hash": "a54178988fafa5d3dcaea73c47e20b30c13b50a2b4dad5a0d131ed00c4fb4f3a",
"source_hash": "b5846d716cde736b1804047aa604a3ec2e9047623dd496bf35f3e2df7958cd13",
"last_changed_at": "2026-05-30T05:50:20.457Z",
"active_status": "active"
}Parsed Structured
{
"language": "en",
"location": {
"raw": "Cambridge, Cambridgeshire, CB22 4WL, United Kingdom",
"city": "Cambridge",
"region": "Cambridgeshire",
"country": null,
"is_remote": false,
"confidence": 0.8
},
"salary_max": null,
"salary_min": null,
"inferred_at": "2026-06-06T10:27:06.610Z",
"launch_scope": {
"reason": "bamboohr_production_catalog",
"included": true,
"location": {
"raw": "Cambridge, Cambridgeshire, CB22 4WL, United Kingdom",
"city": "Cambridge",
"region": "Cambridgeshire",
"country": null,
"is_remote": false,
"confidence": 0.8
},
"countries": []
},
"remote_policy": null,
"salary_period": null,
"workplace_type": "on_site",
"salary_currency": null
}Extensions
{}Native Structured
{
"list_job": {
"id": "101",
"isRemote": null,
"location": {
"city": "Cambridge",
"state": "Cambridgeshire"
},
"atsLocation": {
"city": null,
"state": null,
"country": null,
"province": null
},
"departmentId": "18548",
"locationType": "2",
"jobOpeningName": "Machine Learning Research Engineer",
"departmentLabel": "R&D",
"employmentStatusLabel": "Full-Time"
},
"detail_errors": [],
"detail_job_opening": {
"location": {
"city": "Cambridge",
"state": "Cambridgeshire",
"postalCode": "CB22 4WL",
"addressCountry": "United Kingdom"
},
"datePosted": "2026-03-26",
"atsLocation": {
"city": null,
"state": null,
"country": null,
"countryId": null
},
"description": "<p><span>Constructive Bio is a VC-backed biotechnology startup based in Whittlesford, Cambridge. Our unique technology turns living cells into biofactories, creating sustainable new materials and therapeutics. With full control of the genetic sequence and code, we are exploring chemical space previously unreached by natural biology. </span></p>\n<p><span> </span></p>\n<p><span>Constructive Bio is a spinout from Professor Jason Chin's laboratory at the MRC Laboratory of Molecular Biology in Cambridge. Learn more about the Chin lab achievements here:<br></span><span style=\"color: rgb(11, 79, 209)\"><span style=\"text-decoration: underline\"><a href=\"https://www2.mrc-lmb.cam.ac.uk/ccsb/jason-chin/\" target=\"_blank\" rel=\"noopener noreferrer\">https://www2.mrc-lmb.cam.ac.uk/ccsb/jason-chin/</a></span></span><span><br> </span></p>\n<p><span>We recently secured $58 million Series A fundraising. Read more here: </span><span style=\"color: rgb(11, 79, 209)\"><span style=\"text-decoration: underline\"><a href=\"https://www.constructive.bio/blog/news/constructive-bio-secures-58-million-in-series-a-financing\" target=\"_blank\" rel=\"noopener noreferrer\">https://www.constructive.bio/blog/news/constructive-bio-secures-58-million-in-series-a-financing</a></span></span><span> </span></p>\n<p><span> </span></p>\n<p><span><span style=\"font-weight: bold\">What we’re looking for:</span> </span></p>\n<p><br></p>\n<p><span>We're looking for an ML engineer who can turn prototypes into production systems and work fluidly across the biology-ML boundary. You'll build and maintain our codebase, scale training pipelines, and fine-tune state-of-the-art sequence models on in-house data — all in close collaboration with experimental biologists. This is a frontier role: generative models that directly inform wet-lab design cycles.</span></p>\n<p><span>As our second ML hire, you'll work directly with our ML Scientist to define engineering standards and infrastructure that will shape everything that follows. The role carries real ownership — and real exposure to the full stack of modern biological ML.</span></p>\n<p><br></p>\n<p><span><span style=\"font-weight: bold\">Responsibilities</span></span></p>\n<p><span><br></span></p>\n<ul>\n<li>Implement and benchmark state-of-the-art sequence models (transformers, diffusion models, language models for genomics)</li>\n<li>Build robust experimentation infrastructure: logging, dashboards, hyperparameter sweeps, reproducibility tooling</li>\n<li>Apply fine-tuning protocols on internal biological datasets</li>\n<li>Refactor research code into clean, modular, maintainable systems</li>\n<li>Identify technical gaps and propose solutions — distributed training, data pipelines, inference optimization</li>\n<li>Translate model outputs into formats biologists can interpret and act on; participate actively in cross-functional discussions</li>\n<li>Write well-documented code; participate in code reviews and help set the engineering bar</li>\n</ul>\n<p><span><br></span></p>\n<p><span><span style=\"font-weight: bold\">Requirements</span></span></p>\n<p><span><br></span></p>\n<ul>\n<li>BSc or MSc in an engineering discipline, with demonstrated ML research and development experience</li>\n<li>Hands-on production experience with PyTorch and Hugging Face libraries</li>\n<li>Solid grasp of algorithms, data structures, and software design principles</li>\n<li>Strong communication skills — you're comfortable explaining technical tradeoffs to non-ML collaborators</li>\n<li>Curiosity about biology; willingness to engage seriously with the domain, not just tolerate it</li>\n</ul>\n<p><span><br></span></p>\n<p><span><span style=\"font-weight: bold\">Desirable</span></span></p>\n<p><span><br></span></p>\n<ul>\n<li>Experience in computational biology, particularly sequence or genomic language models</li>\n<li>Publications or open-source contributions in ML or bioinformatics</li>\n</ul>\n<p><span><br></span></p>\n<p><span><span style=\"font-weight: bold\">Why Constructive Bio</span></span></p>\n<p><span><br></span></p>\n<p><span>We're a small, focused team building toward a programmable biomolecules platform. As an early joiner you'll have genuine influence over technical direction, not just execution of a pre-set roadmap. You'll work at the intersection of cutting-edge ML and experimental biology, with direct line of sight from model to experiment to result.</span></p>\n<p><span>We measure success by what works in the wet lab, not what looks good on a benchmark. You'll work directly with experimental scientists to design and test ideas, with a short feedback loop between computation and experiment. That proximity is what makes the work meaningful and demanding. Your models will be evaluated by people who understand the biology deeply, which raises the bar for what good looks like. You'll have a peer in our ML Scientist from day one, but the role requires genuine scientific engagement, not just technical execution.</span></p>\n<p><span> </span></p>\n<p><span>We offer: </span></p>\n<p><span style=\"color: rgb(33, 33, 33)\"> </span></p>\n<ul>\n<li>Newly fitted dedicated site in Whittlesford near Cambridge – on-site parking and regular trains to Cambridge, London and Norwich </li>\n<li>Competitive salary </li>\n<li>Employee share option plan </li>\n<li>25 days holiday plus bank holidays </li>\n<li>Private health insurance </li>\n<li>Pension plan (matching up to 8%) </li>\n<li>Collaborative and pioneering environment, at the leading edge of synthetic genomics and engineered translation </li>\n</ul>\n<p><span> </span></p>\n<p><span>We want to build a team with trust and respect for each other and create a culture of collaboration, openness, curiosity, and scientific excellence.<br><br>We are built on three principles:</span><br><span> </span></p>\n<p><span style=\"color: rgb(33, 33, 33)\"> </span></p>\n<ul>\n<li><span style=\"font-weight: bold\">We imagine:</span><span style=\"font-family: Arial, sans-serif\"><br></span>We think big and plan our own path for success.<br> </li>\n<li><span style=\"font-weight: bold\">We pioneer:</span><span style=\"font-family: Arial, sans-serif\"><br></span>We take action and grow together as one to break moulds.<br> </li>\n<li><span style=\"font-weight: bold\">We deliver:</span><span style=\"font-family: Arial, sans-serif\"><br></span>We take ownership and work together to deliver excellence.<br> </li>\n</ul>\n<p><span> </span></p>\n<p><span>Constructive Bio is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.</span></p>\n<p><span style=\"font-size: 12pt\"> </span></p>\n<p><span style=\"font-size: 12pt\"> </span></p>\n",
"compensation": null,
"departmentId": "18548",
"locationType": "2",
"seekPromoted": false,
"jobCategoryId": null,
"jobOpeningName": "Machine Learning Research Engineer",
"departmentLabel": "R&D",
"jobOpeningStatus": "Open",
"minimumExperience": null,
"jobOpeningShareUrl": "https://constructivebio.bamboohr.com/careers/101",
"employmentStatusLabel": "Full-Time"
}
}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/2bf8e164f44ee8cf648d757e7346314db18ee448?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/9977c51f-45ab-4d07-b8f1-032fe7ebd560JSONGET https://api.bluedoor.sh/job-postings/v1/sources/60069fb1-45f2-4e44-8651-c83dc1a5e008JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/2bf8e164f44ee8cf648d757e7346314db18ee448/eventsJSON