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AI Machine Learning Junior Senior Lead
AI Machine Learning Junior Senior LeadCatalyst Labs • Chicago, Illinois, USA
AI Machine Learning Junior Senior Lead

AI Machine Learning Junior Senior Lead

Catalyst Labs • Chicago, Illinois, USA
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  • [job_card.full_time]
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About Us

Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI Machine Learning and Data Science. We stand out as an agency thats deeply embedded in our clients recruitment operations.

We collaborate directly with Founders CTOs and Heads of AI at Tier 1 VC backed startups scale ups and enterprise tech like Palatir who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise creative problem-solving mindset and long-term growth trajectory in the evolving world of intelligent systems. This is a general / expression of interest therefore by submitting your CV you will be considered for upcoming roles with our clients.

Locations : Most of our client base is concentrated in California New York and a few scattered across other States and Europe.

Who Can Apply : We are looking for professionals with demonstrated experience in AI ML and Data Science roles within reputed tech companies and / or from top 100 universities in the world. Visa sponsorship is available for existing H1b transfers. Student visas will only be considered on the academic pedigree - top 50 global universities.

Experience : From early-career engineers to senior ICs leads and principals.

General Requirements by Role :

Proven experience building or deploying machine learning systems in production environments (not just academic or lab prototypes).

Background in a top technology company Tier 1 VC backed startup advanced research institute or high-caliber engineering team.

Solid understanding of ML fundamentals including model development optimization and evaluation.

  • Hands-on experience with at least one major area of specialization :

LLMs & Generative AI

Computer Vision

NLP / NLU

Reinforcement Learning

Recommendation Systems

Time Series & Forecasting

Applied Deep Learning

  • Familiarity with modern ML engineering workflows :
  • MLOps pipelines

    Model monitoring & observability

    Deployment to cloud or edge environments

    Vector databases & embeddings

    Retrieval-augmented pipelines

    Experience with distributed systems data infrastructure or high-performance computing is a strong advantage.

    Professionals with experience in AI Safety alignment privacy-preserving ML or security-focused ML are also welcome.

    Strong coding proficiency (Python preferred) and familiarity with relevant frameworks such as PyTorch TensorFlow JAX LangChain Ray etc.

    Experience mentoring engineers leading technical initiatives or driving cross-functional collaboration is valued.

    Candidates with a track record of publications open-source contributions patents or shipped products demonstrating real-world impact will stand out.

    Why Work With Us

    Take advantage of the strong relationships we have built with Founders and CTOs.

    Work with recruiters who understand the difference between a fine-tuned model and a foundation model and wont ask if you know Python.

    We prioritize your confidentiality and privacy throughout the recruitment process.

    No Spamming

    Support refining your resume or portfolio specifically for the roles we shortlist you for.

    Direct communication channels. Bypass gatekeepers and speak directly with the actual hiring manager and decision-makers.

    Insight on compensation structures across geographies including equity-heavy offers research-focused roles or hybrid IC / lead tracks.

    Key Skills

    Industrial Maintenance,Machining,Mechanical Knowledge,CNC,Precision Measuring Instruments,Schematics,Maintenance,Hydraulics,Plastics Injection Molding,Programmable Logic Controllers,Manufacturing,Troubleshooting

    Employment Type : Full Time

    Experience : years

    Vacancy : 1

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