{"id":1598810,"url":"https://alion.io/job/devsinc-senior-software-engineer-aiml-3","title":"Senior Software Engineer - AI/ML","company":{"id":3374,"name":"Devsinc","domain":"devsinc.com","url":"https://alion.io/company/devsinc","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":83,"open_postings":16,"ghost_share":0,"stale_share":0.688,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-10-08T05:49:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lahore, Pakistan"],"countries":["PK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":38000,"max_usd":95000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1757},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"MySQL","optional":false},{"name":"NLP","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qdrant","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false},{"name":"Tool Use","optional":false},{"name":"Weaviate","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Celery","optional":true},{"name":"Computer Vision","optional":true},{"name":"Hugging Face","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Kubeflow","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"LangGraph","optional":true},{"name":"LangSmith","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LoRA","optional":true},{"name":"MLFlow","optional":true},{"name":"Multimodal AI","optional":true},{"name":"Ollama","optional":true},{"name":"PEFT","optional":true},{"name":"RabbitMQ","optional":true},{"name":"Ragas","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Redis","optional":true},{"name":"Terraform","optional":true},{"name":"Transformers","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-01T18:46:03Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-09T02:51:52Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Devsinc is hiring a Senior AI/ML Engineer with 4+ years of experience, includingdevelopment of LLM or generative AI applications. The ideal candidate brings strong machine learning fundamentals and expertise in Python backend services and APIs, RAG, semantic search, AI agents, and scalable ML infrastructure, using commercial and open-source models.\nYou will own the end-to-end AI lifecycle, from experimentation and evaluation to deployment, optimization, and monitoring, ensuring reliable, scalable, secure, and cost-efficient solutions. The role also involves architectural decisions, mentoring engineers, and collaborating with clients and cross-functional teams to deliver measurable business impact.\nResponsibilities\nDesign, develop, and deploy AI/ML and LLM-based applications, including AI agents, tool-using systems, and human-in-the-loop workflows, to solve business problems.\nBuild scalable training, fine-tuning, evaluation, and inference pipelines, with experiment tracking and model versioning.\nDevelop and optimize RAG and semantic-search systems using embeddings, document chunking, vector search, reranking, and grounding.\nBuild backend APIs, microservices, and real-time inference services using Python, FastAPI, Flask, or Django.\nImprove model quality, latency, throughput, and cost through experimentation, hyperparameter tuning, quantization, batching, and caching.\nImplement MLOps, automated testing, CI/CD, and production monitoring, supported by evaluation datasets, quality criteria, regression tests, and human review.\nGuide architectural decisions and cloud deployment, ensuring scalability, reliability, security, and resource efficiency, with safeguards against prompt injection, data leakage, unauthorized access, and unsafe outputs.\nEvaluate emerging AI technologies and measure feature effectiveness through product analytics or A/B testing.\nMentor engineers, collaborate with technical and non-technical stakeholders, and document designs, experiments, and outcomes.\nRequirements\nBachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field.\n4+ years of post-graduation professional experience in AI/ML engineering, with demonstrated ownership of production AI systems and hands-on experience developing LLM or generative AI applications.\nStrong production-level Python skills, with hands-on experience in PyTorch and/or TensorFlow and solid knowledge of machine learning, neural networks, NLP, feature engineering, and model optimization.\nExperience integrating commercial or open-source LLMs, including prompt design, structured outputs, tool calling, context management, and model limitations.\nHands-on experience building RAG or semantic-search systems, including embeddings, chunking, retrieval, reranking, and grounding, using vector-search solutions such as pgvector, Pinecone, Weaviate, Qdrant, Milvus, or Elasticsearch.\nExperience developing and deploying APIs, microservices, or inference services using FastAPI, Flask, Django, or equivalent frameworks, with proficiency in SQL and PostgreSQL or MySQL.\nExperience deploying AI solutions on AWS, Azure, or Google Cloud, with working knowledge of Git, Docker, automated testing, CI/CD, and MLOps, including experiment tracking, model versioning, and monitoring.\nUnderstanding of AI evaluation, regression testing, human review, and security and privacy risks.\nAbility to own technical decisions, guide engineers, and communicate effectively with clients and cross-functional stakeholders.\nPreferred Skills & Experience\nExperience with AI frameworks such as LangChain, LlamaIndex, or LangGraph, and evaluation tools such as LangSmith, Langfuse, or Ragas, is a plus.\nExperience with Hugging Face Transformers, vLLM, Ollama, LoRA/PEFT fine-tuning, or self-hosted models is preferred.\nFamiliarity with MLflow, Kubeflow, Kubernetes, Terraform, distributed systems, or GPU acceleration is a plus.\nExperience with data orchestration, asynchronous processing, caching, or messaging, using tools such as Airflow, Redis, Celery, Kafka, or RabbitMQ, is preferred.\nKnowledge of advanced retrieval, knowledge graphs, recommendation systems, computer vision, multimodal AI, or A/B testing and product analytics is a 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