bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesColumbiauniversity1Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)

Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)

Columbiauniversity1 · New York, NY, United States · Active · $2,000–$3,000 / year · SmartRecruiters

Job facts

FieldValue
CompanyColumbiauniversity1
TitleAdjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)
Normalized title-
Department / teamApplied Analytics
LocationNew York, NY, United States
Work model-
Employment typePart Time
Salary$2,000–$3,000 / year
Statusactive
ATS providerSmartRecruiters
Posted / first seen2026-02-27 / 2026-05-31
Changed / last seen2026-05-31 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Columbiauniversity1.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through SmartRecruiters.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in New York.Open
Department jobsActive postings in Applied Analytics.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyColumbiauniversity1
Source252db8b6-df89-482b-953f-2d4f2f975720
ATS providerSmartRecruiters

Description

Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Applied Generative AI. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University. The Applied Generative AI course provides students with a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation. Responsibilities Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions. Evaluate, grade student work and assessments as requested by the course Lecturer. Monitor and address student concerns and inquiries. Columbia University SPS  operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements Graduate degree in an area related to Machine Learning, Computer Science, Applied Mathematics, or related field. 3+ years of related applied professional experience. Preferred Skills & Experience Programming experience in Python and experience with major deep learning frameworks such as PyTorch or TensorFlow. Knowledge of deep learning architectures, such as CNNs, VAEs, GANs, and RNNs. Experience with deploying code on cloud platforms such as AWS, GCP, or Azure. Knowledge of Mathematics and Probability concepts used in machine learning, including Optimization, Gradient Descent, Conditional Probability, Bayes Theorem, and Normal Distribution. Salary range:  $2,000 - $3,000 per semester long course Please submit a resume inclusive of university teaching experience. All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity Employer / Disability / Veteran

Full job record

Job ID1123d0465f430edf7f00ca138c457a607998d56c
Org ID223130e3-59f2-46de-a88c-89229a25e8c2
Source ID252db8b6-df89-482b-953f-2d4f2f975720
Board ID252db8b6-df89-482b-953f-2d4f2f975720
Providersmartrecruiters
Provider Job Key744000111913054
TitleAdjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)
Normalized Title
Statusactive
Activeyes
Location TextNew York, NY, United States
DepartmentApplied Analytics
Team
Employment Typepart_time
Workplace Type
Remote Policy
CountryUnited States
RegionNY
CityNew York
Salary RawColumbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Applied Generative AI. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University. The Applied Generative AI course provides students with a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation. Responsibilities Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions. Evaluate, grade student work and assessments as requested by the course Lecturer. Monitor and address student concerns and inquiries. Columbia University SPS  operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements Graduate degree in an area related to Machine Learning, Computer Science, Applied Mathematics, or related field. 3+ years of related applied professional experience. Preferred Skills & Experience Programming experience in Python and experience with major deep learning frameworks such as PyTorch or TensorFlow. Knowledge of deep learning architectures, such as CNNs, VAEs, GANs, and RNNs. Experience with deploying code on cloud platforms such as AWS, GCP, or Azure. Knowledge of Mathematics and Probability concepts used in machine learning, including Optimization, Gradient Descent, Conditional Probability, Bayes Theorem, and Normal Distribution. Salary range:  $2,000 - $3,000 per semester long course Please submit a resume inclusive of university teaching experience. All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity Employer / Disability / Veteran
Salary Min2,000
Salary Max3,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111913054-adjunct-associate-faculty-applied-generative-ai-on-campus-fall-26-
Apply URLhttps://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111913054-adjunct-associate-faculty-applied-generative-ai-on-campus-fall-26-?oga=true
First Seen At2026-05-31 17:36:11Z
Last Seen At2026-06-06 19:41:36Z
Last Checked At2026-06-06 19:41:36Z
Last Changed At2026-05-31 17:36:11Z
Inactive At
Source Posted At2026-02-27 18:11:47Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=smartrecruiters/board=columbiauniversity1/date=2026-06-06/2026-06-06T19-41-30-851Z-20a34eae43ceee4fdc40a938c901dd77121f850d242397beae458f49d7707da8.json
Event Fields
{
  "content_hash": "9a4a008c4bbcfbe87632b1d7c4bdeb4c7000cb21f99d114169c00aee93044ce8",
  "source_hash": "74e9a3729b7dcee9f84defff9d98549e6e62b8e32d1289a0f19124d4057711eb",
  "last_changed_at": "2026-05-31T17:36:11.977Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "New York, NY, United States",
    "city": "New York",
    "region": "NY",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": 3000,
  "salary_min": 2000,
  "inferred_at": "2026-06-06T19:41:36.096Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "New York, NY, United States",
      "city": "New York",
      "region": "NY",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": "year",
  "workplace_type": null,
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "id": "744000111913054",
  "ref": "https://api.smartrecruiters.com/v1/companies/columbiauniversity1/postings/744000111913054",
  "name": "Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)",
  "uuid": "285d1c4c-1d98-4ac7-abf4-d46a485597f0",
  "detail": {
    "id": "744000111913054",
    "name": "Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)",
    "uuid": "285d1c4c-1d98-4ac7-abf4-d46a485597f0",
    "jobAd": {
      "sections": {
        "jobDescription": {
          "text": "<p>Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Applied Generative AI. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University.</p><p>The Applied Generative AI course provides students with a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation.</p><p><strong><em>Responsibilities</em></strong></p><ul><li><p>Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions.</p></li><li><p>Evaluate, grade student work and assessments as requested by the course Lecturer.</p></li><li><p>Monitor and address student concerns and inquiries.</p></li></ul>",
          "title": "Job Description"
        },
        "qualifications": {
          "text": "<p><strong>Columbia University SPS&#xa0;</strong>operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.&#xa0;</p><p><strong>Requirements</strong></p><ul><li><p>Graduate degree in an area related to Machine Learning, Computer Science, Applied Mathematics, or related field.</p></li><li><p>3+ years of related applied professional experience.</p></li></ul><p><strong>Preferred Skills &amp; Experience</strong></p><ul><li><p>Programming experience in Python and experience with major deep learning frameworks such as PyTorch or TensorFlow.</p></li><li><p>Knowledge of deep learning architectures, such as CNNs, VAEs, GANs, and RNNs.&#xa0;</p></li><li><p>Experience with deploying code on cloud platforms such as AWS, GCP, or Azure.&#xa0;</p></li><li><p>Knowledge of Mathematics and Probability concepts used in machine learning, including</p></li><li><p>Optimization, Gradient Descent, Conditional Probability, Bayes Theorem, and Normal Distribution.&#xa0;</p></li></ul>",
          "title": "Qualifications"
        },
        "companyDescription": {
          "text": "<p>Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society.</p><p>The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.</p>",
          "title": "Company Description"
        },
        "additionalInformation": {
          "text": "<p><strong>Salary range:</strong>&#xa0;$2,000 - $3,000 per semester long course<br>\n<br>\nPlease submit a resume inclusive of university teaching experience.</p><p><strong><em>All your information will be kept confidential according to EEO guidelines.</em></strong></p><p><strong><em>Columbia University is an Equal Opportunity Employer / Disability / Veteran</em></strong></p>",
          "title": "Additional Information"
        }
      }
    },
    "jobId": "3724eb59-0419-43df-b245-b9c4f6284d7c",
    "active": true,
    "company": {
      "name": "Columbia University",
      "identifier": "ColumbiaUniversity1"
    },
    "creator": {
      "name": "",
      "avatarUrl": ""
    },
    "jobAdId": "6b121257-3e66-4de8-8d88-99911fa5c774",
    "applyUrl": "https://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111913054-adjunct-associate-faculty-applied-generative-ai-on-campus-fall-26-?oga=true",
    "function": {
      "id": "education",
      "label": "Education"
    },
    "industry": {
      "id": "higher_education",
      "label": "Higher Education"
    },
    "language": {
      "code": "en",
      "label": "English",
      "labelNative": "English (US)"
    },
    "location": {
      "city": "New York",
      "hybrid": false,
      "region": "NY",
      "remote": false,
      "country": "us",
      "latitude": "40.7127753",
      "longitude": "-74.0059728",
      "fullLocation": "New York, NY, United States"
    },
    "refNumber": "REF1305D",
    "department": {
      "id": 1068780,
      "label": "Applied Analytics"
    },
    "postingUrl": "https://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111913054-adjunct-associate-faculty-applied-generative-ai-on-campus-fall-26-",
    "visibility": "PUBLIC",
    "customField": [
      {
        "fieldId": "5fff0898d102e3515e48905d",
        "fieldLabel": "Course Number",
        "valueLabel": "5560"
      },
      {
        "fieldId": "5ad88b18b60a5e486a2d9efa",
        "valueId": "3bbef67b-e16f-420a-a14b-df988359c43f",
        "fieldLabel": "Employee Job Category",
        "valueLabel": "Faculty Job"
      },
      {
        "fieldId": "5ad9ffd26d8bc56863dd9b7a",
        "valueId": "a01a9441-a122-48d3-8407-45f2155e4fd4",
        "fieldLabel": "Term",
        "valueLabel": "2026 FALL"
      },
      {
        "fieldId": "COUNTRY",
        "valueId": "us",
        "fieldLabel": "Country/Region",
        "valueLabel": "United States"
      },
      {
        "fieldId": "5a945d216d8bc505a492dc8e",
        "valueId": "default",
        "fieldLabel": "Brands",
        "valueLabel": "Columbia University"
      },
      {
        "fieldId": "5abbec096d8bc56863dd96eb",
        "valueId": "2a3b82a0-423d-4062-8348-d4350b7943dd",
        "fieldLabel": "Role",
        "valueLabel": "Associate, Part-time"
      },
      {
        "fieldId": "5a945d216d8bc505a492dc8f",
        "valueId": "1068780",
        "fieldLabel": "Department",
        "valueLabel": "Applied Analytics"
      },
      {
        "fieldId": "5ab2b7b9b60a5e2f7b2c5b2e",
        "valueId": "9a8ca717-4cdc-408a-a528-a1d282c58b19",
        "fieldLabel": "Division",
        "valueLabel": "Masters"
      },
      {
        "fieldId": "5ab2b7766d8bc519b1d9db9d",
        "valueId": "ce0cf7f9-c606-43be-b2ea-374fac2c7fd7",
        "fieldLabel": "Program",
        "valueLabel": "Applied Analytics"
      },
      {
        "fieldId": "5ada008db60a5e486a2d9f4b",
        "valueId": "0c6291f7-c010-4b09-9d2a-5471b248fb56",
        "fieldLabel": "Academic Program",
        "valueLabel": "APAN"
      },
      {
        "fieldId": "5ab3bcdab60a5e2f7b2c5b5c",
        "valueId": "6b516b3e-9a6c-4f1e-8591-f59a3aa5b980",
        "fieldLabel": "Course Modality",
        "valueLabel": "On Campus"
      },
      {
        "fieldId": "6005f3a3e57517446f4f2d3b",
        "fieldLabel": "Section Number",
        "valueLabel": "001"
      }
    ],
    "referralUrl": "https://jobs.smartrecruiters.com/external-referrals/company/ColumbiaUniversity1/publication/285d1c4c-1d98-4ac7-abf4-d46a485597f0?dcr_ci=ColumbiaUniversity1",
    "defaultJobAd": true,
    "releasedDate": "2026-02-27T18:11:47.097Z",
    "experienceLevel": {
      "id": "director",
      "label": "Director"
    },
    "typeOfEmployment": {
      "id": "part-time",
      "label": "Part-time"
    }
  },
  "company": {
    "name": "Columbia University",
    "identifier": "ColumbiaUniversity1"
  },
  "jobAdId": "6b121257-3e66-4de8-8d88-99911fa5c774",
  "function": {
    "id": "education",
    "label": "Education"
  },
  "industry": {
    "id": "higher_education",
    "label": "Higher Education"
  },
  "language": {
    "code": "en",
    "label": "English",
    "labelNative": "English (US)"
  },
  "location": {
    "city": "New York",
    "hybrid": false,
    "region": "NY",
    "remote": false,
    "country": "us",
    "latitude": "40.7127753",
    "longitude": "-74.0059728",
    "fullLocation": "New York, NY, United States"
  },
  "refNumber": "REF1305D",
  "department": {
    "id": "1068780",
    "label": "Applied Analytics"
  },
  "visibility": "PUBLIC",
  "customField": [
    {
      "fieldId": "5ad88b18b60a5e486a2d9efa",
      "valueId": "3bbef67b-e16f-420a-a14b-df988359c43f",
      "fieldLabel": "Employee Job Category",
      "valueLabel": "Faculty Job"
    },
    {
      "fieldId": "5ad9ffd26d8bc56863dd9b7a",
      "valueId": "a01a9441-a122-48d3-8407-45f2155e4fd4",
      "fieldLabel": "Term",
      "valueLabel": "2026 FALL"
    },
    {
      "fieldId": "COUNTRY",
      "valueId": "us",
      "fieldLabel": "Country/Region",
      "valueLabel": "United States"
    },
    {
      "fieldId": "5a945d216d8bc505a492dc8e",
      "valueId": "default",
      "fieldLabel": "Brands",
      "valueLabel": "Columbia University"
    },
    {
      "fieldId": "5abbec096d8bc56863dd96eb",
      "valueId": "2a3b82a0-423d-4062-8348-d4350b7943dd",
      "fieldLabel": "Role",
      "valueLabel": "Associate, Part-time"
    },
    {
      "fieldId": "5a945d216d8bc505a492dc8f",
      "valueId": "1068780",
      "fieldLabel": "Department",
      "valueLabel": "Applied Analytics"
    },
    {
      "fieldId": "5ab2b7b9b60a5e2f7b2c5b2e",
      "valueId": "9a8ca717-4cdc-408a-a528-a1d282c58b19",
      "fieldLabel": "Division",
      "valueLabel": "Masters"
    },
    {
      "fieldId": "5ab2b7766d8bc519b1d9db9d",
      "valueId": "ce0cf7f9-c606-43be-b2ea-374fac2c7fd7",
      "fieldLabel": "Program",
      "valueLabel": "Applied Analytics"
    },
    {
      "fieldId": "5ada008db60a5e486a2d9f4b",
      "valueId": "0c6291f7-c010-4b09-9d2a-5471b248fb56",
      "fieldLabel": "Academic Program",
      "valueLabel": "APAN"
    },
    {
      "fieldId": "5ab3bcdab60a5e2f7b2c5b5c",
      "valueId": "6b516b3e-9a6c-4f1e-8591-f59a3aa5b980",
      "fieldLabel": "Course Modality",
      "valueLabel": "On Campus"
    },
    {
      "fieldId": "5fff0898d102e3515e48905d",
      "fieldLabel": "Course Number",
      "valueLabel": "5560"
    },
    {
      "fieldId": "6005f3a3e57517446f4f2d3b",
      "fieldLabel": "Section Number",
      "valueLabel": "001"
    }
  ],
  "defaultJobAd": true,
  "releasedDate": "2026-02-27T18:11:47.097Z",
  "detail_errors": [],
  "experienceLevel": {
    "id": "director",
    "label": "Director"
  },
  "typeOfEmployment": {
    "id": "part-time",
    "label": "Part-time"
  }
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/1123d0465f430edf7f00ca138c457a607998d56c?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/223130e3-59f2-46de-a88c-89229a25e8c2JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/252db8b6-df89-482b-953f-2d4f2f975720JSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/1123d0465f430edf7f00ca138c457a607998d56c/eventsJSON