Success Story: Strategic RFE Response Leads to I-140 NIW Approval for a Machine Learning Expert
Client’s Testimonial:
"I really liked the attention to detail during the case preparation and the amount of effort taken into fine-tuning it to my profile!”
On February 23rd, 2026, we received another EB-2 NIW (National Interest Waiver) approval for a Machine Learning Engineer in the Field of Machine Learning (Approval Notice).
General Field: Machine Learning
Position at the Time of Case Filing: Machine Learning Engineer
Country of Origin: India
State of Residence at the Time of Filing: California
Approval Notice Date: February 23rd, 2026
Processing Time: 5 months, 5 days (Premium Processing Requested)
Case Summary:
Recently, our firm secured an I-140 NIW approval for a client in the field of machine learning despite a Request for Evidence, with the case filed under Direct Premium Processing. The client holds an M.S. in robotics engineering and presented a proposed endeavor centered on developing advanced machine learning and computer vision techniques to build robust and adaptable perception systems and multimodal AI models for critical U.S. industries.
The Client: Advancing Reliable AI for Critical U.S. Industries
The client’s work focused on improving how AI systems perceive, interpret, and respond across real-world and digital settings. The petition emphasized ongoing research tied to the client’s current employment as a machine learning engineer, including work on robust perception systems. This helped show that the proposed endeavor was not speculative, but part of a concrete and continuing research trajectory with clear U.S. relevance.
The Portfolio: A Focused Record of Technical Contribution
To demonstrate that the client was well-positioned to advance the endeavor, we highlighted a focused but meaningful scholarly record with close to 40 citations and over 10 completed peer reviews. These numbers were not presented as sufficient on their own. Instead, we explained how adjudicators would view them in context: the publication record showed sustained authorship in technical areas directly tied to the proposed endeavor, the citation record reflected that other researchers were relying on the client’s methods, and the peer review activity indicated recognized expertise and professional trust within the field. The petition further pointed to examples showing that the client’s work had informed later research in medical imaging and AI model development, which helped convert raw metrics into evidence of independent reliance.
The Recommendation Letters
We also submitted 2 recommendation letters to reinforce the client’s positioning. The letters supported the importance of the client’s research, described the practical value of the work, and confirmed that the client’s background and accomplishments supported continued progress in the field.
The Challenge: Responding to the RFE
Because this case received an RFE, the response needed to do more than restate credentials. The strength of the case lay in connecting the client’s background, research output, peer recognition, and ongoing work to the national importance analysis under Dhanasar. We demonstrated that the client’s machine learning and computer vision research had implications extending beyond a single employer and could contribute broadly to U.S. technological leadership, public safety, and healthcare innovation. That framing helped show both why the endeavor mattered and why the client was well-positioned to advance it.
We are delighted that this I-140 NIW case was approved and extend our congratulations to the client on this important achievement.