Remote Data Scientist: LLM Fine-Tuning & AI Systems

Arrise Solutions India; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Arrise Solutions India is seeking a Data Scientist (LLM with Fine tuning) for a remote opportunity. You will design and implement advanced algorithms across image, text, audio, and tabular data, and build end-to-end AI/ML systems in a fast-paced environment.

Responsibilities include integrating AI/ML into data pipelines, applying statistical analyses, and collaborating with cross-functional teams to deliver scalable solutions. Strong emphasis on NLP, CV, and large-scale model deployment.

Qualifications

• Experience in statistical analysis, ML and DL techniques, esp. CV and NLP.
• Proven ability to deploy scalable ML models in real-world apps.
• Strong problem-solving and translating business requirements into analytics.

Responsibilities

• Design, develop and implement advanced algorithms using image, text, audio, and tabular data.
• Design large-scale AI/ML systems end-to-end in a fast-paced environment.
• Integrate AI/ML systems into existing data pipelines and systems.
• Apply statistical metrics and ML concepts to drive data-driven decisions.
• Collaborate with cross-functional teams across data and engineering.
• Provide guidance and support to internal teams on data science topics.
• Identify and propose improvements in existing solutions.

Skills

Statistical analysis

Machine Learning

Deep Learning

NLP

Computer Vision

Model deployment

Data at scale

Communication skills

Independent work

Job description

Arrise Solutions India is seeking a Data Scientist (LLM with Fine tuning) for a remote opportunity. You will design and implement advanced algorithms across image, text, audio, and tabular data, and build end-to-end AI/ML systems in a fast-paced environment.

Responsibilities include integrating AI/ML into data pipelines, applying statistical analyses, and collaborating with cross-functional teams to deliver scalable solutions. Strong emphasis on NLP, CV, and large-scale model deployment.